- Email: [email protected]
Freight and logistics
Recent Doctoral Dissertations emission control technologies: pre-catalyst (19381974), catalyst (1975-1980), and closed-loop (19811988). It was found that pre-catalyst and catalyst vehicles utilizing oxygenated fuels had significant reductions in carbon monoxide exhaust levels at 2500 R.P.M. Results for closed-loop vehicles at 2500 R.P.M. showed no significant reductions in carbon monoxide exhaust levels. Further examination of idle data for closed-loop vehicles indicated that a small percentage of these vehicles were considered "grossemitters" based on the 1.5% cut-point set in Colorado. Results of the study indicated that the impact of oxygenated fuels, as well as the rationale for using such fuels as a carbon monoxide reduction strategy, may be difficult to justify as newer, more sophisticated light-duty vehicles comprise a larger proportion of the overall vehicle population in Colorado.
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this algorithm to be very efficient in solving this problem.
Node-Weighted Steiner Tree Problem (NWSTP): It is a natural extension to the Steiner Tree Problem by the addition of node-associated weights. In this dissertation, we concentrate on a special case of NWSTP called Single Point Weighted Steiner Tree Problem (WSTP) suggested by Segev (1987), where the set of nodes, which must be included in the solution tree, consists of a single node, and all node weights are nonpositive. We introduce a T-Set-based algorithm for solving the WSTP. The test results show that our algorithm can not only be used for improving the worst case of Beasley's SST (Shortest Spanning Tree Problem with additional constraints)based algorithm (1987), but is also more efficient.
Extensions of simpliciai decomposition for solving the multicommodity flow problem with bounded arc flows and convex costs. Stefek, Daniel. University of Pennsylvania, 1989. 193 pp. Adviser: Patrick T. Harker. FREIGHTAND LOGISTICS
Efficient algorithms for some combinatorial problems. Tang, Baoxing. University of Pennsylva-
nia, 1990. 107 pp. Supervisor: Marshall L. Fisher. Order Number DA9026658 This dissertation considers three closely related combinatorial optimization problems and proposes efficient algorithms for their solutions. These are: Bulk Pickup~Deliveryproblem: The objective of this problem is to minimize the total transportation cost given a uniform fleet of vehicles at a depot and a collection of customer orders. Each order consists of a certain amount of a bulk product to be picked up and delivered at designated points. Each piece of an order must be assigned to a specific shift, vehicle and driver for transportation. We present an efficient heuristic algorithm based on the solution to a transportation problem, to obtain a feasible solution to the problem. The heuristic has been applied to a real instance of this problem arising in the operations of the Shanghai Truck Transportation Corporation. The test results showed that the gap between the feasible solution ratio (total loaded distance)/(total distance)), and an upper bound on the ratio is about 1.30/0. Generalized Traveling Salesman Problem: It is a particular Traveling Salesman Problem in which the requirement that all cities be visited is relaxed to allow missing cities at a penalty cost. We present an optimization algorithm comprised of a Lagrangean Relaxation algorithm in which tight subtour elimination constraints are dualized into the objective function, various upper bounding procedures, and a Branch-and-Bound strategy. The test results show
Order Number DA9015172 The large-scale multicommodity flow problem with bounded arc flows and convex costs is an important problem which arises in several areas including transportation, telecommunications, and economic equilibrium. Previous research on large-scale nonlinear multicommodity flow problems has focused almost exclusively on the uncapacitated case. Efforts to solve the capacitated case have generally employed penalty methods which cannot handle certain commonly used objective functions and often exhibit extremely slow convergence. In response to the dearth of methods for solving the uncapacitated case, we have developed a general approach for solving this problem called Extended Restricted Simplicial Decomposition (ERSD). This approach is an extension of Restricted Simplicial Decomposition which generates new extreme points by solving shortest path problems rather than computationally demanding linear multicommodity flow problems. We develop two variants of ERSD (ERSD1, ERSD2), and show that they converge to an optimal solution. We then develop H-ERSD2, a variant of ERSD which uses the dual variables from the nonlinear Master problem to generate new extreme points and is more easily implemented than ERSD2. Finally, we show that H-ERSD2 converges to an optimal solution, and we examine the relationship between the methods used by ERSD2 and H-ERSD2 for generating extreme points. We next conducted computational studies of RSD and H-ERSD2. We constructed several capacitated test networks based on three standardized large-scale uncapacitated nonlinear multicommodity flow problems. These test networks vary in the number of capacitated arcs and in the number of acts tight at
Recent Doctoral Dissertations
98
optimality. Computational comparisons of RSD and H-ERSD2 showed that H-ERSD2 performed significantly better than RSD on lightly capacitated networks, and that RSD surpassed H-ERSD2 as the networks became more heavily capacitated. The crossover in the performance of RSD and H-ERSD2 was related to the increase in the time required to solve the nonlinear Master problem as the networks become more capacitated. We also found that H-ERSD2, and to a lesser degree RSD, are sensitive to the maximum allowable number of retained extreme points.
Liability sharing and transport safety: The economics of hazardous materials transportation. Watabe, Akihiro. University of Pennsylvania, 1989. 132 pp. Supervisor: Paul R. Kleindorfer
Order Number DA9015181 Little research has been done on the transportation of hazardous materials as well as hazardous waste generation with the focus on incentives and liabilities shippers and carriers face in managing hazardous transport activities and in sharing resulting liabilities and accident costs. There is also little research which has been done on firms' motivation for reducing hazardous waste and reducing risks arising from liabilities. We, therefore, will address the following three public policy questions on selected economic aspects of hazardous materials transportation and hazardous waste generation: (i) sharing of liabilities associated with transportation accidents and impact on social welfare; (ii) the economics of transport safety; and (iii) the economics of hazardous waste generation, with special reference to incentives for reducing such generation. According to the Coase theorem (1960), under complete information on all risks and protective activities to be undertaken, it can be argued that liability rules and transfer payments are neutral. Nevertheless, the Coase theorem does not hold when either transaction costs or incomplete information are involved. In this dissertation, we will imagine a shipper and a carrier engaged in negotiating transportation fees and liability sharing in the case of accidents. Such bargaining processes are described by optimal auctions and bidding incentive contracts between the shipper and potential carriers. It is then assumed that the shipper has some bargaining power and private information regarding the safety characteristics of carriers which creates either adverse selection or moral hazard. We then consider hazardous waste generation, various monitoring systems and waste-end taxes. These are analyzed from the viewpoint of economic incentives for reducing waste generation and implementing safety operations. The essence of our findings states that, for hazardous materials transportation, joint liability between the shipper and carriers seems more desirable
for social welfare. For hazardous waste generation, monitoring systems will be more effective than waste-end taxes especially when accident liabilities are such that firms do not face bankruptcy as a result of accidents.
Routing and scheduling decisions in the management of hazardous material shipments. Wijeratne, Ajith Buddhikantha. Cornell University, 1990. 208 pp.
Order Number DA9027100 Transportation of hazardous materials (HM) is a growing national problem. The public is becoming more aware of the risk associated with hazardous material shipments. The costs and risk associated with hazardous material transportation are a function of the material, the equipment, the route, and the time during which movement is taking place. Hence, for a given HM and associated equipment, the management of costs and risk involves routing and scheduling shipments. Interests of the carrier, the public authorities and the relevant federal, state and local regulations should be taken into account in routing HM shipments. The carrier is interested in minimizing travel time, operating cost, and accident probability. Public authorities are interested in minimizing risk to the public. The route that minimizes travel time may not minimize risk. Therefore, in some instances, the carrier and the public authorities have conflicting objectives. Federal regulations, while preventing local authorities from banning interstate HM shipments, allow them to impose curfews which makes it necessary to schedule HM shipments in order to minimize curfew delay and other objectives. In the face of limited data on risks and inherent variability in travel time, uncertainty in link and route attributes should be taken into account in routing and scheduling of HM shipments. In this research, a set of analytical tools was created for development of a decision support system for routing and scheduling HM shipments. Specifically: (i) The Stochastic Multi-Objective Shortest Path (SMOSP) algorithm was developed. The SMOSP algorithm is used to find the set of nondominated (based on a partial ordering of attributes) paths in a network that minimize all objectives, where some or all attributes are uncertain. (ii) Risk associated with a link was represented by a series of probabilities that are used as link attributes. These probabilities correspond to occurrence of accidents that result in damages which exceed specified limits. The advantage of this approach is its ability to differentiate between low-probability-high consequence events and high-probability-low consequence events. (iii) The applications of the SMOSP algorithm for routing and scheduling HM shipments was demonstrated by a case study. The validity of results were
99
Recent Doctoral Dissertations verified by simulation. Several guidelines for using the SMOSP algorithm in modeling HM transportation were also developed.
MARITIMETRANSPORTATION Warehouse location under multiple transportation options. Sirisoponsilp, Sompong. University of Maryland College Park, 1989. 207 pp. Director: Jossef Perl.
Priority berthing in congested ports: The application of multiple-attribute decision-making methods. Fararoui, Farzad. University of New South Wales (Australia), 1989.
Order Number DA9021580 The deregulation of the U.S. freight transportation industry has significantly increased the spectrum of transportation options available to shippers, thereby increasing the importance of representing multiple transportation options in the design and analysis of a logistics system. The objective of this study is to develop a methodology for analyzing warehouse location under multiple transportation options. The proposed methodology recognizes and represents the interdependence between facility location, transportation, and inventory decisions. The problem of warehouse location under multiple transportation options, termed the Combined Warehouse Location-Transportation Problem (CWLTP), is defined as that of determining the number and locations of warehouses, and the "optimal" transportation options between plants and warehouses, such as to minimize total distribution cost. The proposed C W L T P model differs from existing warehouse location models in three important aspects. First, it considers the selection of transportation options as output rather than input. Second, it includes an explicit representation of the inventory implications of warehouse location and transportation decisions. Thirdly, it explicitly represents the required level of customer service. The CWLTP is a complex mixed integer problem which cannot be solved directly using existing optimization techniques. We develop a heuristic algorithm for solving the CWLTP, which is based on decomposing the CWLTP into two subproblems. Each of the two subproblems is shown to be a component of the CWLTP. With appropriate simplifications, the first subproblem is reduced to a linear mixed integer problem, and is solved exactly. The second subproblem is solved exactly using an implicit enumeration scheme. We show that the CWLTP solution algorithm provides valid solutions to a sample of test problems of different sizes, and produces reasonable responses to changes in company policy and in the environment in which the company operates. It is also shown that a simultaneous optimization of warehouse location and transportation decisions can lead to a significantly lower total distribution cost than a component-by-component approach in which warehouse location and transportation decisions are determined independently.
The effectiveness of a port is adversely affected by the congestion that impacts on port operation, trade, and economic development of the nation. Consequently, it is increasingly important that a comprehensive short-term solution be provided for coping with the problem in a timely, cost-effective, and relatively simple manner. This thesis aims at providing such a solution. It analyzes port congestion by considering all possible components of congestion cost and prospects for immediate to short-term solutions. It also demonstrates how to transform the recognition of congestion into an effective operating system that optimizes the so called generalized social cost of congestion. The research, in general, and the "optimization process," in particular, are carried out in the light of "multiple-attribute decision making" techniques. The approach taken in this thesis starts with the identification of the main areas of the costs of congestion followed by skepticism about the efficiency and effectiveness of the traditional scheme of "first come first served," the scheme which has long been used as a principal guideline in port operation. It then reviews the recent development of the multiple attribute decision making techniques in a search for the most suitable method(s) to the problem. After a critical examination of the wide range of available multi-attribute decision making methods, two techniques-Simple Additive Weighting (SAW) and Techniques for Order Preferences by Similarity to Ideal Solution ( T O P S I S ) - a r e selected for preference ranking of the available alternatives for serving the waiting vessels, in light of the "minimum cost service" objective. Although the overall optimization process is a straightforward task, it was found that because of the complexity of the mathematical operations there was a need for the application of computer programs to handle the optimization. Therefore, a computer software package "CONPORT" was developed for this research. This package is capable of optimizing the generalized social cost of congestion according to the two selected multiple-attribute decision making methods SAW and TOPSIS. The general conclusion of the research is that the traditional scheme of "first come first served" cannot always be efficient in combating the congestion problem, and the system of "priority berthing," when coupled with the multiple-attribute decision making techniques, can provide a "static optimum system."
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this algorithm to be very efficient in solving this problem.
Node-Weighted Steiner Tree Problem (NWSTP): It is a natural extension to the Steiner Tree Problem by the addition of node-associated weights. In this dissertation, we concentrate on a special case of NWSTP called Single Point Weighted Steiner Tree Problem (WSTP) suggested by Segev (1987), where the set of nodes, which must be included in the solution tree, consists of a single node, and all node weights are nonpositive. We introduce a T-Set-based algorithm for solving the WSTP. The test results show that our algorithm can not only be used for improving the worst case of Beasley's SST (Shortest Spanning Tree Problem with additional constraints)based algorithm (1987), but is also more efficient.
Extensions of simpliciai decomposition for solving the multicommodity flow problem with bounded arc flows and convex costs. Stefek, Daniel. University of Pennsylvania, 1989. 193 pp. Adviser: Patrick T. Harker. FREIGHTAND LOGISTICS
Efficient algorithms for some combinatorial problems. Tang, Baoxing. University of Pennsylva-
nia, 1990. 107 pp. Supervisor: Marshall L. Fisher. Order Number DA9026658 This dissertation considers three closely related combinatorial optimization problems and proposes efficient algorithms for their solutions. These are: Bulk Pickup~Deliveryproblem: The objective of this problem is to minimize the total transportation cost given a uniform fleet of vehicles at a depot and a collection of customer orders. Each order consists of a certain amount of a bulk product to be picked up and delivered at designated points. Each piece of an order must be assigned to a specific shift, vehicle and driver for transportation. We present an efficient heuristic algorithm based on the solution to a transportation problem, to obtain a feasible solution to the problem. The heuristic has been applied to a real instance of this problem arising in the operations of the Shanghai Truck Transportation Corporation. The test results showed that the gap between the feasible solution ratio (total loaded distance)/(total distance)), and an upper bound on the ratio is about 1.30/0. Generalized Traveling Salesman Problem: It is a particular Traveling Salesman Problem in which the requirement that all cities be visited is relaxed to allow missing cities at a penalty cost. We present an optimization algorithm comprised of a Lagrangean Relaxation algorithm in which tight subtour elimination constraints are dualized into the objective function, various upper bounding procedures, and a Branch-and-Bound strategy. The test results show
Order Number DA9015172 The large-scale multicommodity flow problem with bounded arc flows and convex costs is an important problem which arises in several areas including transportation, telecommunications, and economic equilibrium. Previous research on large-scale nonlinear multicommodity flow problems has focused almost exclusively on the uncapacitated case. Efforts to solve the capacitated case have generally employed penalty methods which cannot handle certain commonly used objective functions and often exhibit extremely slow convergence. In response to the dearth of methods for solving the uncapacitated case, we have developed a general approach for solving this problem called Extended Restricted Simplicial Decomposition (ERSD). This approach is an extension of Restricted Simplicial Decomposition which generates new extreme points by solving shortest path problems rather than computationally demanding linear multicommodity flow problems. We develop two variants of ERSD (ERSD1, ERSD2), and show that they converge to an optimal solution. We then develop H-ERSD2, a variant of ERSD which uses the dual variables from the nonlinear Master problem to generate new extreme points and is more easily implemented than ERSD2. Finally, we show that H-ERSD2 converges to an optimal solution, and we examine the relationship between the methods used by ERSD2 and H-ERSD2 for generating extreme points. We next conducted computational studies of RSD and H-ERSD2. We constructed several capacitated test networks based on three standardized large-scale uncapacitated nonlinear multicommodity flow problems. These test networks vary in the number of capacitated arcs and in the number of acts tight at
Recent Doctoral Dissertations
98
optimality. Computational comparisons of RSD and H-ERSD2 showed that H-ERSD2 performed significantly better than RSD on lightly capacitated networks, and that RSD surpassed H-ERSD2 as the networks became more heavily capacitated. The crossover in the performance of RSD and H-ERSD2 was related to the increase in the time required to solve the nonlinear Master problem as the networks become more capacitated. We also found that H-ERSD2, and to a lesser degree RSD, are sensitive to the maximum allowable number of retained extreme points.
Liability sharing and transport safety: The economics of hazardous materials transportation. Watabe, Akihiro. University of Pennsylvania, 1989. 132 pp. Supervisor: Paul R. Kleindorfer
Order Number DA9015181 Little research has been done on the transportation of hazardous materials as well as hazardous waste generation with the focus on incentives and liabilities shippers and carriers face in managing hazardous transport activities and in sharing resulting liabilities and accident costs. There is also little research which has been done on firms' motivation for reducing hazardous waste and reducing risks arising from liabilities. We, therefore, will address the following three public policy questions on selected economic aspects of hazardous materials transportation and hazardous waste generation: (i) sharing of liabilities associated with transportation accidents and impact on social welfare; (ii) the economics of transport safety; and (iii) the economics of hazardous waste generation, with special reference to incentives for reducing such generation. According to the Coase theorem (1960), under complete information on all risks and protective activities to be undertaken, it can be argued that liability rules and transfer payments are neutral. Nevertheless, the Coase theorem does not hold when either transaction costs or incomplete information are involved. In this dissertation, we will imagine a shipper and a carrier engaged in negotiating transportation fees and liability sharing in the case of accidents. Such bargaining processes are described by optimal auctions and bidding incentive contracts between the shipper and potential carriers. It is then assumed that the shipper has some bargaining power and private information regarding the safety characteristics of carriers which creates either adverse selection or moral hazard. We then consider hazardous waste generation, various monitoring systems and waste-end taxes. These are analyzed from the viewpoint of economic incentives for reducing waste generation and implementing safety operations. The essence of our findings states that, for hazardous materials transportation, joint liability between the shipper and carriers seems more desirable
for social welfare. For hazardous waste generation, monitoring systems will be more effective than waste-end taxes especially when accident liabilities are such that firms do not face bankruptcy as a result of accidents.
Routing and scheduling decisions in the management of hazardous material shipments. Wijeratne, Ajith Buddhikantha. Cornell University, 1990. 208 pp.
Order Number DA9027100 Transportation of hazardous materials (HM) is a growing national problem. The public is becoming more aware of the risk associated with hazardous material shipments. The costs and risk associated with hazardous material transportation are a function of the material, the equipment, the route, and the time during which movement is taking place. Hence, for a given HM and associated equipment, the management of costs and risk involves routing and scheduling shipments. Interests of the carrier, the public authorities and the relevant federal, state and local regulations should be taken into account in routing HM shipments. The carrier is interested in minimizing travel time, operating cost, and accident probability. Public authorities are interested in minimizing risk to the public. The route that minimizes travel time may not minimize risk. Therefore, in some instances, the carrier and the public authorities have conflicting objectives. Federal regulations, while preventing local authorities from banning interstate HM shipments, allow them to impose curfews which makes it necessary to schedule HM shipments in order to minimize curfew delay and other objectives. In the face of limited data on risks and inherent variability in travel time, uncertainty in link and route attributes should be taken into account in routing and scheduling of HM shipments. In this research, a set of analytical tools was created for development of a decision support system for routing and scheduling HM shipments. Specifically: (i) The Stochastic Multi-Objective Shortest Path (SMOSP) algorithm was developed. The SMOSP algorithm is used to find the set of nondominated (based on a partial ordering of attributes) paths in a network that minimize all objectives, where some or all attributes are uncertain. (ii) Risk associated with a link was represented by a series of probabilities that are used as link attributes. These probabilities correspond to occurrence of accidents that result in damages which exceed specified limits. The advantage of this approach is its ability to differentiate between low-probability-high consequence events and high-probability-low consequence events. (iii) The applications of the SMOSP algorithm for routing and scheduling HM shipments was demonstrated by a case study. The validity of results were
99
Recent Doctoral Dissertations verified by simulation. Several guidelines for using the SMOSP algorithm in modeling HM transportation were also developed.
MARITIMETRANSPORTATION Warehouse location under multiple transportation options. Sirisoponsilp, Sompong. University of Maryland College Park, 1989. 207 pp. Director: Jossef Perl.
Priority berthing in congested ports: The application of multiple-attribute decision-making methods. Fararoui, Farzad. University of New South Wales (Australia), 1989.
Order Number DA9021580 The deregulation of the U.S. freight transportation industry has significantly increased the spectrum of transportation options available to shippers, thereby increasing the importance of representing multiple transportation options in the design and analysis of a logistics system. The objective of this study is to develop a methodology for analyzing warehouse location under multiple transportation options. The proposed methodology recognizes and represents the interdependence between facility location, transportation, and inventory decisions. The problem of warehouse location under multiple transportation options, termed the Combined Warehouse Location-Transportation Problem (CWLTP), is defined as that of determining the number and locations of warehouses, and the "optimal" transportation options between plants and warehouses, such as to minimize total distribution cost. The proposed C W L T P model differs from existing warehouse location models in three important aspects. First, it considers the selection of transportation options as output rather than input. Second, it includes an explicit representation of the inventory implications of warehouse location and transportation decisions. Thirdly, it explicitly represents the required level of customer service. The CWLTP is a complex mixed integer problem which cannot be solved directly using existing optimization techniques. We develop a heuristic algorithm for solving the CWLTP, which is based on decomposing the CWLTP into two subproblems. Each of the two subproblems is shown to be a component of the CWLTP. With appropriate simplifications, the first subproblem is reduced to a linear mixed integer problem, and is solved exactly. The second subproblem is solved exactly using an implicit enumeration scheme. We show that the CWLTP solution algorithm provides valid solutions to a sample of test problems of different sizes, and produces reasonable responses to changes in company policy and in the environment in which the company operates. It is also shown that a simultaneous optimization of warehouse location and transportation decisions can lead to a significantly lower total distribution cost than a component-by-component approach in which warehouse location and transportation decisions are determined independently.
The effectiveness of a port is adversely affected by the congestion that impacts on port operation, trade, and economic development of the nation. Consequently, it is increasingly important that a comprehensive short-term solution be provided for coping with the problem in a timely, cost-effective, and relatively simple manner. This thesis aims at providing such a solution. It analyzes port congestion by considering all possible components of congestion cost and prospects for immediate to short-term solutions. It also demonstrates how to transform the recognition of congestion into an effective operating system that optimizes the so called generalized social cost of congestion. The research, in general, and the "optimization process," in particular, are carried out in the light of "multiple-attribute decision making" techniques. The approach taken in this thesis starts with the identification of the main areas of the costs of congestion followed by skepticism about the efficiency and effectiveness of the traditional scheme of "first come first served," the scheme which has long been used as a principal guideline in port operation. It then reviews the recent development of the multiple attribute decision making techniques in a search for the most suitable method(s) to the problem. After a critical examination of the wide range of available multi-attribute decision making methods, two techniques-Simple Additive Weighting (SAW) and Techniques for Order Preferences by Similarity to Ideal Solution ( T O P S I S ) - a r e selected for preference ranking of the available alternatives for serving the waiting vessels, in light of the "minimum cost service" objective. Although the overall optimization process is a straightforward task, it was found that because of the complexity of the mathematical operations there was a need for the application of computer programs to handle the optimization. Therefore, a computer software package "CONPORT" was developed for this research. This package is capable of optimizing the generalized social cost of congestion according to the two selected multiple-attribute decision making methods SAW and TOPSIS. The general conclusion of the research is that the traditional scheme of "first come first served" cannot always be efficient in combating the congestion problem, and the system of "priority berthing," when coupled with the multiple-attribute decision making techniques, can provide a "static optimum system."