A historic review of management science research in China

Omega 36 (2008) 919 – 932 www.elsevier.com/locate/omega

A historic review of management science research in China夡 John Wanga,∗ , Ruiliang Yanb , Kimberly Hollistera , Dan Zhuc a Department of Management & Information Systems, Montclair State University, Montclair, NJ 07043, USA b School of Business, P.O. Box 9209, Virginia State University, Petersburg, VA 23806, USA c Iowa State University, Ames, IA 50011, USA

Received 14 January 2007; accepted 31 October 2007 Available online 3 December 2007

Abstract The development of management science (MS) in China has been a long and dynamic journey involving many unexpected events. Beginning in 1955 and continuing through the present, the revolution roughly consisted of four stages. The first stage (1955–1965) was characterized by large-scale campaigns. Critical path method (CPM) and optimum seeking method swept the country resulting in astonishing economic efficiencies. The Cultural Revolution halted MS during the second stage (1966–1976). The third stage (1977–1992), began when the door to the outside world was officially opened, but half-closed due to Tiananmen Incident later, and re-opened again owing to spirit of Deng Xiaoping’s speech in Southern China. The fourth stage (1992–present) has pushed MS into almost every field, accelerating national modernization. The impact of research by many scholars is evidenced through history by examples that include conducting war, building dams, and developing postal service routes. 䉷 2007 Elsevier Ltd. All rights reserved. Keywords: Management science (MS); Optimum seeking method; Chinese postman problem; Gray system theory; DEA/preference structure model

1. History The early systematic formulation of operation research (OR) began in Great Britain as an independent discipline about 60 years ago. In the days that eventually led to World War II, the British Air Ministry was facing the pressing challenge of the formidable Air Force of Nazi Germany. Figuring out how to best deploy the Royal Air Force to protect the homeland of Britain had 夡

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fax: +1 973 655 7678. E-mail addresses: [email protected] (J. Wang), [email protected] (R. Yan), [email protected] (K. Hollister), [email protected] (D. Zhu). 0305-0483/$ - see front matter 䉷 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.omega.2007.10.004

forced the British to scientifically and quantitatively study the strategic and tactic problems involved in military operations [1]. After WWII, OR displayed tremendous growth and expansion. The marriage of OR and general management into management science (MS) has brought it far from its origin of military operations and into our daily lives. Many scholars visualize OR and MS interchangeably because they usually are studied concurrently. There are at least eight major OR academic journals being published at the present time. In addition, academic institutions all over the world have established their own MS/OR department. One of the most prevalent scenes in MS/OR is the constant tweaking of OR principals and algorithms to solve social or economic problems.

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1.1. Some ancient traces MS is a cross-functional, multi-disciplinary examination of advances and solutions supporting enhanced strategic planning, executing, controlling, feedbacking, and managing in the modern business world. It is interesting to note that some non-business applications of its principles can be seen most ancient cultures. In Ancient China, in his epic novel “Romance of the Three Kingdoms” (220–280 AC), the Chinese writer Guanzhong Luo vividly depicted applications of many of the operations management principles in ancient warfare. Traces of the same principles can be seen in the popular Chinese book of Tzu Sun’s “The Art of War” (300 BC) which touched on many topics including logistical management and resource management [2]. A real life example of MS can be seen in the Dujiang Dam irrigation project; the oldest large-scale irrigation project in the history of the world. It has been supporting people in Sichuan Province, China, for more than 2000 years. Why is the Dujiang Dam so durable? It is a historical wonder of science and technology as well as an excellent example of how human beings can live in harmony with nature. In the year 256 BC, during the Warring States Period (475–221 BC), Li Bing and his son directed the construction of the Dujiang Dam to control flooding on the Chengdu Plains in Sichuan Province [3]. After more than 2264 years, this brilliant achievement in water conservancy made rationalized irrigation supply, flood diversion, and sand discharge possible. Still today, the dam plays a tremendous role in this regard. People could not survive without this! The Dujiang Dam project is a terrific example of using nature and science in harmony. The entire Dujiang Dam project was built on nature and completely dissolved in it. All things with a shape are living beings and have a life history. Their lives all have a process of formation, settlement and degeneration. When something can completely dissolve into nature, its life will certainly connect with nature. If nature does not degenerate, its life will not degenerate. These are all key factors in Dujiang Dam’s durability. The Dujiang Dam is composed mainly of “flowing cages.” These “cages” are made of bamboo, which have been previously soaked in oil and lime. This pre-treatment enhances their fiber’s stretching force and its resistance to rot. Several one foot by more than three feet wide cages are made out of this pre-treated bamboo. Then they fill the cages with scree, to build “flowing cages.” Every year they are checked and any decaying cages are replaced with new ones. This method seems extremely simple, but we will see the brilliancy of it.

Li Bing was a founder of many great ideas and was a founding father of some of our most popular management principles. Maintenance has been done on the dam annually since it was first built. When building Dujiang Dam, Li Bing, one of the dam’s founders, put a stone meter in the inner river to be used as the depth gage for removing sand during annual maintenance. The principle idea of this maintenance was to “dig sands deep and build dams low.” “Dig sands deep” means to dig down to the level of the stone meter. Otherwise, the water volume in the inner river will not be enough for irrigation. “Build dams low” means that the dam cannot be built too high. Otherwise it might cause problems diverting floods and overflow. In contrast to the ridiculous idea of “manpower overrides the heavens,” when human beings and nature care about each other, humans are then living in harmony with nature. This principle seems to be easily abandoned in this era of modern science. The lesson seems so simple, yet it is very profound. For example, many irrigation experts from Germany, England, France, America, and other western countries came to visit Dujiang Dam during the civil war. They believed that replacing the “flowing cages” was too troublesome. The experts proposed to build a concrete dam using principles of modern mechanics. However, the concrete dam collapsed soon after it was built. Experts had to restore the original dam, using the original technique of Li Bing and his son. It is fortunate that they did not succeed in changing the dam, so that this inter-living and inter-caring relationship between humans and nature could continue. On the other hand, these early ideas lack the quantitative mathematic analysis characterized by the modem MS. 1.2. Early developments After the establishment of the People’s Republic of China in 1949, certain war techniques of MS were studied and used in China. Despite its immediate usefulness as an academic discipline, MS has been distrusted due to its association with western corporate capitalism. As early as the mid 1950s, Xuesen Qian, the socalled “father of the Chinese atom bomb” and other scholars who returned to their homeland (mainly from the US after 1949), introduced MS/OR in China. At first, OR was translated directly by the words: OR, and later by the meaning: “Yun-Chou Xue”: the science of planning and maneuvering. Then, in 1957, linear programming (LP) began appearing in architecture, textile industries, and many other fields. In 1958, a significant effect was achieved particularly in transportation, the

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loading–uploading of materials, and the dispatching of vehicles. For instance, the diagrammatic decomposition method, a more convenient method than the traditional one, was initialized. In the early 1960s, a group of mathematicians joined the ranks of research and application of MS/OR. Headed by Loogeng Hua (a famous scholar), a special group visited each province to demonstrate and spread the project management technology and the optimum seeking method. After that, dramatic economic efficiency was realized across the entire country, along with international recognition. From 1965 on, the critical path method (CPM) and the program evaluation and review technique (PERT) gradually penetrated all sectors, from architecture to agriculture and forestry to the petroleum industry. In the 1970s, the methods of optimization design were used in the design of optics, ships, aircrafts, architectural structures, electronic circuits, and chemical engineering processes. In the mid 1970s, queuing theory was used in mine transportation, telecommunications, seaports, and computer designs. After the 1970s, non-linear programming (NLP) began catching people’s attention, making major contributions in improving the quality of product design. Unfortunately, several political campaigns, especially the Cultural Revolution, had seriously damaged the growth of MS in China. The distrust and suspicion to the western world intensified and the field of MS was rejected almost entirely. The only notable exception is some applications of LP were cautiously used by the Central Planning Committee and attached to the central government. 1.3. Education Most managers, especially high-ranking officials, were nominated from party members, but not professionals as soon as the Communist party controlled the power in China. Loyalty to the party was the paramount standard for the appointment and promotion of managers. In place of science, management was treated as a revolution. In the early 1950s, “learning from big brothers of the (former) Soviet Union” was a popular slogan and a prejudiced policy in China. Management education in universities and colleges started in the middle 1950s. At this time, only a few management majors in institutions of higher education, such as the Harbin Institute of Technology, offered the related courses. Even Tsinghua University (a Chinese equivalent of MIT) and Beijing University (a Chinese equivalent of Harvard) did not offer a single management major.

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History took a surprising turn in 1976, with the passing away of Chairman Mao. The notorious “gang of four” was soon arrested and China once again shifted its focus onto economic development, rather than spreading revolutionary ideology. By 1978, the central government announced a new and ambitious “Four Modernizations” plan to modernize its science, industry, agriculture, and defense. Universities all over China were encouraged to apply advanced sciences and technologies from the west. By early 1979, formal programs of study (that include MS and OR) were established at a number of Chinese universities in Beijing, Shanghai, and many other cities. The State Economic Planning Committee introduced 18 methods (which included LP, PERT, the optimum seeking method, etc.) in the 1980s in order to spread modern management knowledge. Various training classes and special seminars for high-level management personnel were conducted. MS/OR did not become a required course for most economics and management students until the early 1980s. As basic theories received more emphasis, combined with the use of computer software and case studies, MS/OR as a major was growing in popularity. In the early days of MS/OR in China, their faculties were dispersed among departments of mathematics, systems engineering, industrial management, industrial engineering, or computer sciences. The presence of MS/OR in schools of business was established more recently. Chinese universities and research institutions have been historically independent from industries and businesses, which is very different from their foreign colleagues. Positions are mostly held in private enterprises. This has propelled the public perception of MS/OR as being very “academically oriented” and “mathematical.” As a result, the Chinese OR Society (CORS) affiliates itself to the Institute of Applied Mathematics (IAM) in the Chinese Academy of Science. In most established OR departments, professors and researchers are mathematicians by training. However, the situations have changed recently due to a greater number of foreign educated professionals finding their way back to the mainland, bringing with them formal training and practical knowledge [4]. 2. Theoretical breakthroughs 2.1. The Chinese postman problem (CPP) The CPP was first proposed by Mei-Ko Kwan, a Chinese mathematician in 1962 [5]. It was a question heard around the world, since it is a common problem in a real life environment. The question was that given a postal

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zone with a number of streets that must be served by a postal carrier, how does one develop a tour that covers every street in the zone and brings the postman back to his point of origin, having traveled the minimum possible distance? In general, any problem that requires that all of the edges of a graph be traversed at least once while traveling the shortest total distance overall is a CPP. The CPP has many real world applications which are much beyond the original postal carrier scenario. For instance, we can treat those problems like the inspection of pipes, cable or optic fibers, street cleaning, garbage collecting, meter reading, etc. as CPPs [6]. Certainly, the CPP has its roots in the origins of mathematical graph theory. In 1736, Leonid Euler’s famous analysis of a popular puzzle of that time on the Königsberg bridge problem, the mathematician demonstrated a forerunner’s contribution [7]. Researchers who have followed Kwan’s initial work have since developed many variants of the original CPP. In the CPP, the edges have no direction; otherwise it will become the directed postman problem. In the directed postman problem, each of the edges has a direction associated with it. The mixed postman problem refers to a graph that contains a mixture of both directed and undirected edges. In this case, a subset of the edges in the graph must be traversed and the situation becomes the NP-hard rural postman problem. Also, the capacitated CPP admits restrictions, with each edge’s non-zero demand and a limited capacity of postmen for supplying service. The Hierarchical CPP (HCPP) is a variant of the classical CPP, in which the arcs are partitioned into clusters and a precedence relation is defined on the clusters. Practical applications of the HCPP include snow and ice control on the roads and determination of optimal torch paths in flame cutting. The HCPP is NP-hard in general, but polynomial-time solvable if the precedence relation is linear and each cluster is connected. For this case, an exact algorithm, requiring a lower computational effort than previous procedures, is described recently by Ghiani and Improta [8]. 2.2. Optimum seeking method The optimum seeking method was created by the Chinese mathematician Loogeng Hua in the 1960s [9–11]. In 1953, J. Kieffer, an American mathematician, discovered that seeking experiment points according to the rule of the golden section would make it possible to reach the optimal state the fastest. His discovery was then refined by Loogeng Hua, who turned it into the optimum

seeking method, or the 0.618 method. The method was popularized in China for a time [12] and such a campaign, based on the human-wave tactic, produced definite impact. This episode demonstrated the prospect of applying the rule of the golden section in spheres other than the arts. Even before the emergence of the notion of consciously grasping the rule of the golden section, people have repeatedly applied it to their own spheres of practice on the basis of their instincts. The amazing campaigns and battles in the history of war provide clear applications of the rule of the golden section; examples of conforming to this rule are seen throughout the military realm. For example, the shadow of 0.618 can be seen in such examples ranging from the arc of the cavalry sword to the apex of the flying trajectory of a bullet, shell, or ballistic missile. Also, 0.618 is displayed from the optimum bomb-release altitude and distance for an aircraft in the dive bombing mode to the relationship between the length of the supply line and the turning point in a war. 2.3. Gray system theory In 1982, Deng introduced the gray system theory (GST). This multi-disciplinary theory deals with those systems for which we lack information. Examples of such systems can be found in agriculture, economics, meteorology, hydrology, ecology, and management. The fields covered by GST include system analysis, data processing, modeling, prediction, decision-making and control [13]. Numerous national academic conferences on GST have been organized since 1984. The methods of the gray system have been used to determine the general planning for rational development in science, technology, society, and economy throughout the China. A special course entitled, “GST and applications”, has been offered in many universities and colleges. “The Journal of Gray System” was issued internationally. “Gray System (Society, Economy)”, the first book about this theory, was published by the Chinese Defense Industry Press in 1985 [14]. From 1985 to 1988, Huazhong University of Science and Technology Press issued “Gray Control System,” “Gray Forecasting and Decision-Making,” “Fundamental Methods of the Gray System,” and “Multi-Dimensional Gray Programming” [15–17]. Penetration of GST into traditional mathematical programming is a powerful algorithm when there is a shortage of historical data. Written by Sifeng Liou and Tianbang Guo, “Gray System: Theory and Application,” is based on the technical transformation of the industrial

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system and research on decision-making for food production in Henai Province. This book demonstrated gray LP, gray 0-1 programming, gray NLP, etc. with computer programs. There are four cases regarding incomplete system information: incomplete element (parameter) information; incomplete structure information; incomplete boundary information; and incomplete operation behavior information. The gray number, of which we only know a rough range but not the exact number, is the basic element of the gray system. A gray number is an internal set or a number set. Gray system analysis, modeling, forecasting, programming, and controlling are the main subjects of research for GST. Regarding reasoning logic and problem solving, GST is entirely different from probability theory. The main targets of research are: gray number, gray unit, and gray relationship. Gray number and its operations, gray matrix, and gray equation are the basics of GST. All probabilistic numbers are treated as gray numbers within a certain range. No matter how complicated the system or how scattered the data are interior rules still exist. GST determines the rules among the data, but does not look for a probability distribution. The method of data generation, which includes generation through accumulated addition or subtraction, makes seemingly disordered data showing a certain degree of regularity. Generation through accumulated addition: Let X (0) = {X (0) (1)},

i = 1, n.

Then the data series are: X (1) (1) = x(0)(1), X (1) (k) = X (1) (k − 1) + X (0) (k), E.g.

X(0)

1 < k N .

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up with a series of LP models for evaluating the performance of homogeneous entities (schools, hospitals, business firms, etc.) that convert inputs into outputs. In 1996, Joe Zhu proposed the DEA/preference structure model [19]. In his paper, Zhu noted the importance of considering the DMUs or decision maker’s preference over the potential adjustments of various inputs and outputs when DEA is employed. Zhu developed some weighted, non-radial CCR models by specifying a proper set of “preference weights.” These “weights” reflect the relative degree of desirability of the potential adjustments of current input or output levels. It is shown that the preference structure prescribes fixed weights (virtual multiplier bounds) or regions that invalidate some virtual multipliers, hence generating preferred (efficient) input and output targets for each DMU. In addition to providing the preferred target, the approach gives a scalar efficiency score for each DMU to secure comparability. It is also shown how specific cases of his approach handle non-controllable factors in DEA and measure allocative and technical efficiency. In addition, Zhu has intensified his model and developed the related software [20–22]. 3. Some original practical applications A variety of practical models and principles have been applied in different industries and services in China. The following are some works carried out inside the mainland by Chinese researchers. It should be noted that there is very little information available regarding actual implementation of these models making it is hard to tell whether they had an actual effect in changing the underlying operations.

= {3.278, 3.337, 3.39, 3.679, 3.85},

X(1) = {3.278, 6.615, 10.05, 13.684, 17.534}.

3.1. CPM/PERT

As to gray LP (GLP): when solving the GLP, C(), A(), the gray numbers, need to be “whitened.” Based on the historical data of b1 (), a GM (1, 1) model can be formed. The forecasting values of b1 (s + k), i = 1, 2, . . . , n, can be calculated and used to replace b. Then the general LP solving methods can be used [18].

In the early 1960s, Xuesen Qian used PERT for research and management of missiles in the Chinese space program. Loogeng Hua had accelerated the national application of CPM in the management of projects, construction, and in the maintenance and repair of large equipment. Starting in the 1970s, the application of computer software simplified tedious calculations and draft drawing of the network. Since the imported software did not match Chinese visualization, the Northwestern University of Technology and the Beijing Institute of Computer Technology each developed PERT software with better graphics in the middle 1980s. Given the input node number and simulating the manual way, “CPERT Network Calculation—Graphics Program System” can produce various time parameters

2.4. Data envelopment analysis (DEA)/preference structure model DEA was introduced by Abraham Charnes and William W. Cooper in 1978. This method is used to identify and analyze relative efficiency of decisionmaking units (DMU). In the 1980s, DEA was introduced as a new domain of OR in China. It was set

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and critical path(s), balance resources, optimize results, and draw a chart with Chinese ideographs automatically. A network of up to 300 nodes can be designed in a PC, which satisfies the needs of most projects. Later in the 1980s, Jiangsu Province sponsored a research project entitled “Planning Management and Decision-Making Supporting System for Large Scale Projects.” This project allowed for databases to become the center of data collecting, counseling, statistics summarizing, and chart printing. Efficiency had been improved by dynamic management and the control of networks. Sijun Bai’s book, “Computer-Aided Analysis for Activity Network Planning,” addresses design principles, methods, implementation and programming, skills of computer-aided network parameters analysis, time, cost, and resource optimization. The practice of using computers as an aid to the activity network analysis and design in project management practice was also discussed. In accordance with the input data and precedence relationship, this software had the following functions: it automatically determines the node number for each activity; calculates ES, EF, LS, LF with given relationships or nodes; draws network, time, and bar charts from given nodes; compromises between time and cost; optimizes resources for network planning; optimizes time; transforms time and calendar; prints report tables; and manages files. Assuming each activity and cost parameter follow normal distribution, Hougui Zhou developed a GERT model in 1989 for installing a temporary bridge over the upper stream of the Gerzhou dam [23]. This GERT was a new development of CPM/PERT. This development caught the attention of Chinese engineers and managers since it can be beneficial for making decisions properly, distributing resources reasonably, simulating the production process, and solving stochastic problems. 3.2. Mathematical programming Xiangyun Gui conducted a research project covering 16 oil fields, 46 refineries, 30 consumption zones, and 19 kinds of petrochemical products for the Institute of the Petrochemical Industry [24]. Gui set up a large-scale mathematical programming model containing 17 hundred and 21 variables and 921 constraints. Six main products needed to be distributed and transported based on the equilibrium of production and consumption. A computer system was formulated which included databases for the optimal distribution of oil, the optimal transportation of petrochemical products, operating flows, programs and models, and the systemic

dictionary lexicon. The economic gain was 2–4 × 108 Yuan. Kejun Guo and Rulong Wang [25], of the Institute of Computer Techniques of Hunan Province, simplified the complex processes of a refinery as the following: input of oil → transformation and treatment → output of products. Their model contained seven types of constraints: (1) the balance of materials; (2) the amount of added hydrogen; (3) the quantity of products; (4) the quarto of diesel and gasoline; (5) the quality of products; (6) the consumption of energy; and (7) selfconsumption of fuel. The objective was to maximize the net profit. This model is very general and easy to use in the normal design of production procedures, the formation of production plans, and in intermediate and long term strategic planning. Zhong Li [26] used a model of two-stage dynamic programming (DP) to automatically decide the direction of cables in electrical power plants. In modern electrical power plants, cables were crossover installed along channel brackets. If each cross-connection point of channel brackets is treated as a node and the brackets for each workshop, which are connected through nodes, are treated as a bracket network or a cable channel network; the problem of cable routes becomes the selection of the shortest feasible path among the cable channel networks, given related technical requirements. The size of modern electrical power plants is so big that over 400 network nodes and more than 6000 cables need to be installed. Through this model, the average orientation time for each cable was reduced by 99.83% to 2 s. Also, many engineers were interested in using NLP for optimal design in the 1980s. 3.3. Multiple objective decision-making Based on personal preferences and assigned weights, goal programming (GP) gives decision makers a range of optional plans with a certain degree of freedom. GP is very popular with practitioners as decision makers choose their most satisfactory solution. Jingyan Chen [27] identifies an application of GP to the case of solving the composition of cotton mixing among 240 kinds of raw cotton. Chen’s model gives six priorities based on six physical indicators of raw cotton, consisting of grade, length, spot, strength, spinning number, and fineness; the incomplete collection of raw cotton due to warehouse capacity limitations and gross cost is also taken into consideration. The use of the GP solution helped a cotton spinning factory with 21 varieties of raw cotton readily meet the requirements of quality, quantity, and the cotton-mixing cycle time of 20 days saving

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the factory 0.03 Yuan per kilogram of cotton. When the total factory production of 1.7 × 104 ton of cotton per year is considered, the economic savings is substantial. The introduction of the analytic hierarchy process (AHP) (Thomas L. Saaty, 1971) into China raised the interest of MS/OR practitioners in governmental decision-making, business administration, transportation, energy resources, education, and merchandising. A special journal on “Decision-Making and AHP” was published to stimulate theoretical research and academic interchanging. In other more recent work, fuzzy set theory has been used to analyze situations without sufficient data. Qualitative evaluation and quantitative analysis have been combined resulting in work more applicable to China’s situation. Based on 36 basic environmental elements, Xiujuan Yuan [28] constructed a four-level model that was evaluated through the Delphi Method. A weight table, consisting of 22 natural environmental elements and 14 socioenvironmental elements produced results that were much more accurate than previous guess-work. Based on an LP model forage composition, Jianping Zhang [29] introduced the “may be less than” fuzzy objective function for gross price and “may be more than” fuzzy constraints with their member function. As a result, the feasible ranges for change were decided and a fuzzy LP formulation can be solved with traditional LP methods. The solutions can be restricted to the pre-determined ranges and problems related to LP hard constraint can be circumvented. 3.4. Other models Population explosion, especially in developing countries, has been a big concern worldwide. Implementing strategies of how to control this growth of population and set a goal for growth is a basic national policy in China. “The Forecasting and Control of Population,” written by Jian Song, is a representative work of the related research. Differential equations and other mathematical tools were used to describe the process of population growth and the birth–death rate. Based on census information, the author analyzed different birth rates and gave the respective levels of Chinese population after the year 2000. For instance, one of the synthesized analyses is if the average birth rate remained at 1.5, the gross national population would achieve 1.13 billion and would not begin to decrease until the year 2028. The results played a big role in Chinese population decision-making for the government. In order to determine the general goal of population growth, Wang [30] developed a new concept and related

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method on “degree of possibility-satisfaction.” The optimum population was analyzed in respect to land, water, air pollution, energy resources, food, fish, and economic development. Twenty factors were evaluated based on the analysis of the degree of possibility-satisfaction, including the need of food per capita, the need of energy resources per capita, and the need of living space per capita. The six scenarios and the related indicators of degree of possibility-satisfaction by the year 2080 had also been explored. The concepts and methods of this book can also be conveyed into other fields. System dynamics (SD) has been employed to formulate the aggregate quantitative model of national society and economy, which consists of 18 sub-systems with more than 550 equations. Applications of MS are everywhere: from scheduling bulk-pickup-delivery vehicles in Shanghai [31] to analytical models of strategic structure for development of sciences and technology and their applications [32]; to the PC aided network technique [33]; and to green supply chain management (GSCM) in China [34]. Modeling methods have been widely adopted in the past 30 years, especially in socioeconomic and managerial areas. In 1990, the State Council’s Institute of Development sponsored the research project of “China in the year 2000.” The results were published, in an 800,000 word report, concerning the complicated topics and questions about the economic development in China. The project posed many great questions such as: How to achieve the strategic goal of triple GNP? How to deal with the proportional relationship of accumulation and consumption? What are the effects of technical progress on the national economy? The following are some completed national models: • the econometric model, • multi-divisional expanded reproduction, • population and economy coordination development, • the quantitative analysis model of economic structure, • long-term development trends, • the middle to long-term macroeconomic model, • the national education planning model, • energy resources supply systems and decisionmaking, • energy resource supply and demand, • environmental prediction, and • production structure of national agriculture. Many MS tools have been used in the development and solution of these models; methods include:

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mathematical programming, recursive programming, state evolution simulation technique, Cobb–Douglas Function (to analyze technical progress), AHP, SD, Leontief’s input–output model, and conception of reasoning from analogy (CRA). CRA combines traditional engineering project analogy technique with modern forecasting methods. LP was used to analyze and optimize the supply of coal, electricity and oil with demand for the purpose of setting strategic goals for energy resource development. GP was employed to optimize the overall distribution and planning of energy resource supply systems. Integer programming (IP) was manipulated to determine the exploitation and disposition of energy resource supply locations. The future’s uncertainty is a predicament. Stochastic elements and uncontrollable factors make long-term planning extremely difficult. The combination of different models has been used to reduce the risk in planning under uncertainty. Four large-scale LP models, with each having more than 3000 variables and 100 constraints, were set up in a project to develop an optimal production plan for crops and livestock in a country of Shandong Provence [35]. Gray Theory was then utilized to improve the optimal plan’s robustness to weather conditions. The application of mathematical programming requires significant data; which can be an obstacle in modeling real systems. Since the interruption of 10year havoc in China, lack of data is a typical problem. Allowing Fuzzy Set and Gray Theory to penetrate into traditional mathematical programming is an interesting development helping to alleviate the data scarcity issue. At the same time, multiple criteria decision-making has been attracting more and more attention. 4. Some recent contributions 4.1. New models and algorithms In GP problem, the balance between general equilibrium and optimization is difficult to achieve. To address this, Hu et al. [36] at Shanghai Jiao Tong University propose a generalized varying-domain optimization method for fuzzy GP (FGP) incorporating multiple priorities; they present three varying-domain optimization methods. Co-evolutionary genetic algorithms (GAs), called GENOCOPIII, are used in the solution of the problem. The generalized varyingdomain optimization method used by Hu et al. has other real-world decision-making applications. In recent years, artificial neural networks which offer the advantage of clearer visualization have attracted

considerable attention. Computer scientists and engineers are developing neural network representations of existing problems for which new or alternative solutions can be generated. Li and Li [37] and Li and Xu [38] demonstrate the flexibility of neural networks for modeling and solving diverse mathematical problems including Taylor series expansion, Weierstrass’s first approximation theorem, LP with single and multiple objectives, and fuzzy mathematical programming. Neural network representations of these problems may help to overcome current limitations in finding their solutions. Li [39] also discusses neural network representation of linear fuzzy LP problems. Novel solutions to variations of the general DEA model have also been sought. Chen [40] examines the non-linear imprecise DEA (IDEA) model which occurs when multiple inputs and outputs consist of imprecise data such as bounded data, ordinal data or ratio bound data. Chen addresses the non-linearity of the resulting problem by either using scale transformations or variable alternations to convert it into a linear program or by solving it by using standard DEA by converting imprecise data into a set of exact data. In later work, Chen [41,42] proposes a modified superefficiency DEA model which addresses infeasibility issues in the super-efficiency DEA model to correctly capture super-efficiency represented by the input saving or the output surplus. Wang et al. [43] propose a projection method for solving a system of non-linear monotone equations with convex constraints. Under standard assumptions, the authors show the global convergence and the linear convergence rate of the proposed algorithm. Preliminary numerical experiments show that this method is efficient and promising. To address issues in unimodal optimization, Pan [44] develops an alternative search plan to the golden ratio search with a “platinum ratio” of around 0.55. In a simulation study Pan shows that the golden ratio search is the best only in the sense of zero variation, but not for minimizing cost. Li et al. [45] advocate the application of the equateto-differentiate rule, an alternative to the family of expected utility theory, to the prisoner’s dilemma. Also, the authors have successfully tested the theoretical prescriptions derived from theoretical developments in six experiments. 4.2. Applications in policy-making Regional economic issues in China have been modeled by Zheng et al. [46]. Their work applies the basic

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models of Gini and variation coefficients to analyze the effect of time on China’s regional economic differences. Their work resulted in forecasting China’s regional economic differences as well as providing results for the adaptive control of regional per-capita income levels which can be used to determine an acceptable level of income inequality for policy making. Hua et al. [47] estimate the ecological efficiency of paper mills along the Huai River in China. The model, which describes a new approach to defining reference sets, provides efficient input/output targets for DMU managers to improve DMUs’ efficiencies. The model was validated with data from 32 paper mills along the Huai River in China. While deterministic input–output analysis has been applied to solving a variety of economic problems, stochastic models, which account for uncertainty, provide a better representation of real decision-making. Wu and Chang [48] developed a solution methodology for the stochastic input–output model using geneticalgorithm-based (GA-based) gray mathematical programming techniques. They apply their methodology to a model in assessing the impacts of recent pollution charges and water resource fees to a textile–dyeing factory. Their research findings indicate that gray input–output analysis is an applicable tool for the evaluation of environmental cost impacts needed for corporate production planning and management. Li et al. [49] attempt to model country performance in the Olympic Games. Previous models which applied conventional DEA failed to capture the impact of economic status on the number of gold, silver, and bronze medals earned by each country. Li et al. [49] use a context-dependent assurance region (AR) DEA model to analyze the achievements of nations during six summer Olympic Games taking into account economic status. Multiple sets of AR restrictions were incorporated into the DEA. As a result, a fair comparison of different nations is achieved. It is shown that by scaling up or down the outputs, multiple AR restrictions of different groups of nations can be transformed into a common set of AR restrictions that is applicable to all nations. 4.3. Applications in manufacturing In the current environment of technological innovation, diversity in demand, and intensifying market competition; the development of cost effective scheduling systems has attracted a lot of attention. Tang and Liu [50] elaborated on a real-life order scheduling problem for the production of steel sheets in Baosteel. The problem was formulated as a separable mixed IP model.

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The objective was to determine the starting and ending times of critical bottleneck operations for each order to minimize the sum of weighted completion times of all orders subject to capacity constraints and complicated precedence constraints. Tang and Liu [50] developed a decomposition solution methodology based on Lagrangian relaxation, LP, and heuristics to address the problem. In addition to developing a novel formulation and solution methodology for the problem, Tang and Liu developed a production order scheduling simulation system for Baosteel. The simulation system’s functionality included initial managing and scheduling of orders using the simulation and then the manual adjustment of schedules. In an effort to encourage modernization in business, the Chinese government has adopted a policy to separate the management and ownership of state-owned enterprises. Currently, state-owned enterprises’ contract system (SECS) is the leading enterprise management system used in China today. Feng and Xu [51] provide insight into the impact of various managerial strategies on encouraging cooperation between the enterprise and state to maximize outcomes. Their overall objective is discovering how to encourage enterprises to engage in independent business decision-making with the goal of enhancing their operational capabilities while pursuing technological innovation and long-term business growth. Another issue involving manufacturing is the largescale effort to upgrade production and operations management systems of major iron and steel companies in China. Traditionally, production scheduling is done using a greedy serial method which results in very high setup costs. Tang et al. [52] propose a parallel strategy to model the scheduling problem and solve it using a new modified GA (MGA). As in the simulation developed by Tang and Liu [50], Tang et al. [52] combine output from an operations model with manual interaction to develop a scheduling system. Utilization of their model in Shanghai Baoshan Iron & Steel Complex resulted in 20% improvement in 1 year over the previous manual based system. The rescheduling of production lines is a common and frustrating problem for manufacturing firms. Disturbances come from many sources including: incorrect work, machine breakdowns, rework due to quality problem, or rush orders; disturbances are difficult to predict due to their fuzzy and random nature. To address this issue, Li et al. [53] develop a production rescheduling expert simulation system; their system integrates many techniques and methods, including simulation, artificial neural networks, expert knowledge, and

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dispatching rules. The system developed by Li et al. [53] was deployed in a Chinese manufacturing firm with satisfactory rescheduling results. Railroad dispatching is another area within the manufacturing sector that has attracted OM attention. To address both the yards’ output objective and the customer service on-time objective, He et al. [54] developed a fuzzy mathematical model to handle the conflicting objectives. They employed a hybrid approach of GAs and local search techniques to develop a solution. In validating their model, they conducted a test on a practical problem. When compared to results published in an earlier study, the results from their problem indicated that it is a promising method for analyzing the railyards’ dispatching problem. Uncertainties in manufacturing are common; Xu et al. [55] address the robust stabilization problem for uncertain systems with delayed states. In their work they develop two approaches for addressing the stochastic nature of systems. A linear matrix inequality (LMI) approach is used to achieve robust stability solutions in the case of a nominal unforced system. For another class of systems with uncertainties in delay, solutions are developed using linear memoryless state feedback control. Fuzzy systems are now used to describe the major scientific domain that began with fuzzy set theory. Applications of fuzzy systems can be seen in many areas including both manufacturing and agriculture. Recent years have seen significant research in the area of fuzzy control systems. Tang et al. [56] propose an adaptive control algorithm, based on the fuzzy parameter identification. Their algorithm can be applied to a class of time-varying systems in which conventional control techniques have been used for many years. Wang [57] considers the effects of learning and deterioration on single-machine scheduling problems. Wang’s work demonstrates that when the learning effect is introduced with deteriorating jobs (i.e., jobs whose processing times are an increasing function of their starting time) the solution to the single-machine time-minimization scheduling problem remains polynomially solvable. Wang and Xia [58] address no-wait or no-idle flow shop scheduling problems with deteriorating jobs. They assume a simple linear deterioration function with some dominating relationships between machines. Li et al. [59] consider flow shop scheduling problems with flowtime minimization. In order to reduce the CPU time of flowtime computation to 33.3%, which is the main computational burden of most heuristics, they employ general flowtime computing (GFC). In related

work, He [60] introduces a general algorithm, called ALG, for online and semi-online scheduling problem. 4.4. Applications in supply chain management Research in the area of supply chain management has grown considerably in recent years. Quality improvement is a key topic in improving supply chain functionality. Zhu et al. [61] investigate the interactions between quality-improvement decisions and operational decisions such as the buyer’s order quantity and the supplier’s production lot size. They explore the impacts of multiple parties in improving quality in the supply chain. For example, the buyer’s quality standards have significant impact on the profits of both the buyer and the supplier. Buyers cannot cede all responsibilities for quality improvement to the supplier. The incorporation of risk preferences when establishing supply chain coordination contracts is very important. Choi et al. [62] address the issue of quantifying different risk preferences for the retailer and supply chain coordinator in a vertically integrated two-echelon supply chain under a stochastic demand environment; they propose the use of the MV (mean-variance) formulation. Choi et al. [62] demonstrate how the supply chain coordinator can set a wholesale price for achieving channel coordination with respect to the specific risk preference of the retailer. The greening of the supply chain is an important concern for many business enterprises and a challenge for logistics management. Zhu et al. [63] investigate the correlation of organizational learning and management support with the extent of adoption of GSCM practices in Chinese manufacturing firms. In all cases considered, both inbound and outbound logistics activities are potential polluters to the environment. Zhu et al. [63] confirm that, after controlling for a number of outside influences, there is a significant positive relationship between organizational learning and management support and the greening of the supply chain. To reflect the retailer’s power in supply chain management, Hua and Li [64] propose retailer-dominant non-cooperative game models for the newsvendor problem by introducing the sensitivity of the retailer’s order quantity to the manufacturer’s wholesale price. Hua and Li [64] use the Nash bargaining mode to investigate two cooperative scenarios between a manufacturer and a retailer in a two-echelon supply chain. The impact of cost and demand disruptions on the supply chain is an important area of study. Xiao and Qi [65] study the coordination problem for a supply chain with two competing retailers. They focus on the

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impact of both cost disruption and demand disruptions on supply chain coordination mechanisms. Li et al. [66] examine the impact of postponement strategy on a manufacturer in a supply chain with planned backorders. In their research, they demonstrate that using postponement strategy can result in a lower total average cost under certain circumstances. Li et al. [66] identify that the variance of the machine utilization rates and the variance of the backorder costs are key factors in making postponement decisions. A product mix flexibility model considering flexibility in labor, machine, routing, and information technology is developed by Gong and Hu [67]. Outputs from the model can be useful in making production decisions for multiple products under uncertainty. The developed mode can also assist in making enterprise flexibility promotion decisions. Ding and Chen [68] model coordination in a single period, three level supply chain that sells short life cycle products. In their model, the contract between the downstream firms is negotiated before the contract with upstream firms. Ding and Chen [68] construct a flexible return policy by postponing the determination of the final contract prices and only setting pricing rules. They conclude that multi-level supply chain can be fully coordinated if each pair of adjacent firms implements flexible return policies. Zhang et al. [69] evaluate a more general three-tier linear supply chain model via simulation and provide an approach to quantify the value of shared shipment information. Their model aids supply chain managers evaluate cost–benefit trade-offs during information system construction. In managing a multiple source, multiple product supply chain, another difficult question to address is how to simultaneously determine the optimal number of suppliers to use and how to optimally allocate order quantity to each of these suppliers. The decision can be further complicated by the consideration of supplier capacity constraints and the multi-criteria nature of the supplier selection problem. Xia and Wu [70] propose an integrated analytical hierarchy process approach improved by rough sets theory and multi-objective mixed IP. 4.5. Applications in services Chinese research in MS/OR has made significant improvements in the Chinese rail systems. Prior to the computerization of the national railroad system, railways worked off a fixed optimized schedule; a delay of

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just one train produced a cascading delay on many later trains. Today, the Ministry of Railways has real-time information on its network of more than 5000 railway stations and the more than 2000 trains that depart daily [71]. With real-time information, the ministry can respond quickly to minimize the impacts of unexpected delays and temporary demand “hiccups.” In practical situations, queuing systems face a great deal of uncertainty. The precise values of many parameters are not known precisely; consequently, the minimal expected total cost per unit time becomes fuzzy. To address the fuzzy nature of cost coefficients and actual arrival rates, Chen [72] proposes a mathematical programming approach to find the membership function of the fuzzy minimal expected total cost per unit. Chen’s work is based on Zadeh’s extension principle. Solutions to Chen’s model provide decision makers with more information for designing queuing systems. Service organizations face complex issues in developing staffing plans. Li and Li [73] present a multi-skilled staff planning model that considers staff flexibility. Prior research failed to capture the balance of cost and benefits of staff flexibility in developing staff planning models. Li and Li [73] apply multi-objective GP to analyze several diversified goals in the case of staff planning at a Chinese clinic; their model can be applied to many types of service organizations. Developing comprehensive maintenance and replacement plans in the transportation services sector is a dynamic and multiple time-period problem. Lai et al. [74] address this issue with the application of the sequential method to determine optimal policies for implementing preventive engine maintenance or engine replacement. Lai et al. [74] use engine data from the Kowloon Motor Bus Company Limited in Hong Kong to test their model. The sequential approach to the problem considered states in an engine’s lifetime and the response of each state to corrective maintenance. Using their model, three optimal maintenance and replacement policies with respect to three different criteria were determined. The financial services sector faces uncertainty in optimal portfolio selection. Following the idea of Markowitz’s mean variance model, Li and Xu [75] develop a model to address the fuzzy nature of the problem. Their model incorporates both the judgment of experts and the subjective opinions of investors in future securities. Using real data from the Shanghai Stock Exchange, Li and Xu [75] demonstrate that their portfolio selection model generates an efficient frontier based upon the investor’s degree of optimism regarding investments.

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5. Trends Clearly one of the most obvious trends in the short MS/OR history has been its dramatic increase in its popularity in China. MS/OR has been either an odd obsession of “Ivory Tower” mavericks or high stake decision-making that affects the lives of millions [76]. Today, with the widespread software availability and endless supply of college educated workers, MS/OR has become an overnight success. Private enterprise is increasingly feeling the squeeze of fierce competition and the ever-increasing cost of labor and raw material and is turning to MS/OR in search of higher operations efficacy and competitive advantages. Most of these private enterprises willingly accept the fact that change, sometimes rather difficult ones, have to be made to survive in the present Chinese economic system. State-owned strategic manufacturing and service industries (such as steel, petrochemical, banking, and railroad), have also witnessed widespread adoption of MS/OR principles in production scheduling, supply chain management, delivery, and inventory management. The Chinese economic life has been dominated by state owned enterprises and as a result most MS research and practical applications have been conducted within these enterprises. It was not until very recently that purely private enterprises were also involved in MS research and most importantly in its practical applications. Most MS research has been conducted with fairly well-defined mathematical models and optimization objectives, which have resulted in measurable performance improvements. The explosive growth in the information technology industry and information networks has made it possible to make near real-time optimization and increase MS/OR flexibility [77]. We can see this in examples all over the world. The rigid social structure and the Chinese tendency of categorical formalism have also hindered the MS/OR development. This rigidness occurs both in the academic and practical realms. From the “the Four Modernizations” to “Ten Do’s and Do Not’s” to “Four Thoughts,” the Chinese fondness of such paradigms is endless. The traditional division between academic research and labor has encouraged researchers to perform mainly pure mathematical studies. Until a short time ago, papers on practical implementation on MS/OR have been deemed “unfit” to be published in major academic journals. Maybe this was back in the book burning days! This was considered due to the “lacking of theoretical study.” How unfortunate! Luckily, Chinese society has gone through transformational changes recently. It is pleasing and wonderful to see

the relaxation of traditional formalism and increasing popularity of practical research [78,79]. We have witnessed the promising trend of increasing awareness of the importance of operational efficiency. Workers have shown increased willingness toward changes and new ideas. MS/OR research in foreign subsidiaries located in China has been the bright side of Chinese MS/OR history. Unburdened by ambiguous ownership and conflicting interests that is common in most state owned enterprises, most MS/OR projects have been very promising and successful. These foreign subsidiaries also have the advantage of greater flexibility in accessing foreign MS/OR workers and information technologies [80]. The other trend, which is unique to the Chinese, is the re-vitalization of traditional Chinese wisdom. Do not fix something that is not broken! Today, MS/OR workers in China have recognized that most MS/OR projects are multi-dimensional problems and encompass many areas such as mathematics, sociology and, management. Most MS/OR workers have found themselves inevitably involved in persuading behavioral changes and balancing conflicting interests. It is in this context that most Chinese workers resort to ancient wisdoms to make MS/OR more user “friendly.” Due to their wisdom, the unique combination of modern MS/OR and traditional Chinese thinking made the changes appear just, adhered to the social norms, and within the confinement of the social structure. These approaches undoubtedly increased the effectiveness of MS/OR in China. 6. Conclusion There have been many discoveries, enlightenments, and real world applications due to the hard work of many scholars. The development of MS/OR has been expanding since the mid 1900s. To sum up, the earliest known public sector of MS/OR research in China dates back to the mid-1950s. Initial MS/OR research concentrated on practical applications such as transportation and textiles. In the 1960s, with the establishment of the economic and mathematics group in the Institute of Mathematics of the Chinese Academy of Science, preliminary research was carried out on combining MS/OR with national economic planning. The Cultural Revolution brought MS/OR to a standstill for almost 10 years until it ended in the 1970s. Finally, progress was made in the 1970s when MS/OR started being applied in state owned enterprise planning and management. Input–output analysis was used in national planning and the control of population growth, which is a huge issue for China. We witnessed the proliferation of

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practical application in the academic world in the mid1980s. There are many application areas which include energy, population, agriculture, environment, ecology, national economic planning, defense, business administration, large-scale scientific projects, education, and traditional Chinese medical science. China’s history is spectacular and they have made great contributions to the world. From the origins of civilization to the present day, 4000 years of China’s history is amazing. There are about 20,000 researchers in the Fuzzy Set Theory arena around the world, half of them are Chinese! The potential contribution of Chinese scholars to the area is very optimistic. MS/OR has been and will be playing a significant role in China’s four modernizations and harmony society! References [1] Kirby MW. Operational research in war and peace: the British experience from the 1930s to 1970. Imperial College Press; 2003. [2] Bartholdi J. Operations research in China. Interfaces 1986; 16(2):24–30. [3] Li Y. Retrieved from http://www.pureinsight.org/pi/index.php? news = 942; 2001. [4] Zhu Z. Towards user-friendly or: a Chinese experience. Journal of the Operational Research Society 2002;53(2):137–48. [5] Kwan MK. Graphic programming using odd or even points. Chinese Mathematics 1962;1:273–7. [6] Stewart WR. Chinese postman problem. In: Gass SI, Harris CM, editors. Encyclopedia of operations research and management science. 2nd ed., Norwell, MA: Kluwer Academic Publishers; 2001. [7] Christofides N. The optimal traversal of a graph. Omega 1973;1:719–32. [8] Ghiani G, Improta G. An algorithm for the hierarchical Chinese postman problem. Operations Research Letters 2000;26(1): 27–32. [9] Hua LK. The theory of numbers. New York: Springer; 1981. [10] Hua LK, Yu XJ. Optimization. Beijing, China: The Science Press; 1982. [11] Hua LK. In: Halberstam H, editor. Selected papers. New York: Springer; 1983. [12] Xu K, Lao HS. Popularization of the “Double Method”: a landmark in science-oriented management of China. Studies in Science of Science 2000;2:27–32. [13] Deng JL. Introduction to gray system. Journal of Grey System 1989;1(1):1–24. [14] Deng JL. Grey system (society, economy). Beijing: The Chinese Defense Industry Press; 1985. [15] Deng JL. The basic methods of gray system. Wuhan: Huazhong University of Science and Technology Press; 1988. [16] Deng JL. Grey control system. Wuhan: Huazhong University of Science and Technology Press; 1985. [17] Deng JL. Grey forecasting and decision making. Wuhan: Huazhong University of Science and Technology Press; 1985. [18] Deng JL. Contrasting gray system theory to probability and fuzzy. ACM Sigice Bulletin 1995;20(3):3–9.

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