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An efficient search strategy for site-selection decisions in an expert system
Abstracts in Location Science
198
Locating vehicle inspection stations to protect a transportation
network
M. John Hodgson, Kenneth E. Rosing and Jianjun Zhang Geographical Analysis Vol. 28, No. 4, 1996, pp. 299-314
We develop a new conceptual
approach to locating inspection stations for hazardous vehicles,
prevention, and compare it to the previous, punitive, philosophy of the flow-capturing location model.
We implement this preventive protection philosophy with a new mixed integer program that maximizes hazard avoidance by locating a number of inspection stations to detect and remove hazardous vehicles as early in their trips as possible. We test the model’s performance and analyze the spatial characteristics of solutions simulating several potential applications. Our computations demonstrate that a relaxed integer-linear program is overly demanding computationally and that a simple greedy heuristic lacks robustness. We suggest further approaches to developing more powerful and efficient solution methods.
A computational
method for market area analysis on a network
Atsuyuki Okabe and Masayuki Kitamura Geographical Analysis
Vol. 28, No. 4, 1996, pp. 330-349 This paper shows a computational method for market area analysis assuming that stores and consumers are distributed over a network and the distance between two points on the network is given by the route distance. First, we consider five basic questions often raised in market area analysis, and show a general method, called the network transformation method, that gives an intuitive way of looking at computational methods for solving these questions. Second, assuming that consumers follow the Huff model, we consider four questions concerning market area delineation and market potential often discussed in market area analysis in practice. We show that the network transformation method is also useful to develop computational methods for solving these questions. One of the notable results is that market area delineation of the Huff model (which is analytically difficult to obtain on a plane) can be exactly obtained on a network.
Using simple genetic algorithms to calibrate spatial interaction models G. Diplock and S. Openshaw Geographical Analysis Vol. 28, No. 3, 1996, pp. 262-279
The paper investigates the use of two genetic algorithms in an attempt to obtain globally optimal parameter estimates for a mix of simple and complex spatial interaction models. The genetic algorithms work well and are strongly advocated as a more robust approach particularly for use with the more complex multiparameter models where the differences in both performance and parameter values are judged to be significant.
An efficient search strategy for site-selection decisions in an expert system Theo A. Arentze, Aloys W. J. Borgers and Harry J. P. Timmermans Geographical Analysis
Vol. 28, No. 2, 1996, pp. 126-146 This paper describes an algorithm for spatial search, which is used in an expert system for site selection. The algorithm, named ProfMat, is able to find the best site in the area of interest even when the number of possible sites is large and many decision criteria are involved. Compared to commonly used search procedures, ProfMat improves the efficiency of spatial search in two ways. First, the best site is identified through an iterative rather than a linear process of selection and
Abstracts in Location Science
199
evaluation of optional sites. Second, an area is searched by narrowing down the focus to increasingly smaller areas and, thus, sites are evaluated as much as possible groupwise. The ProfMat procedure is illustrated by analyzing the problem of retail site selection. A comparison with alternative search procedures shows that ProfMat considerably reduces the evaluation costs needed to find the best site. The implementation of the algorithm in an expert system shows how ProfMat can be used in combination with specialist’s knowledge to solve site-selection problems. The efficiency of the procedure allows considering large sets of optinoal sites, so that it may improve the quality of the outcome.
A cost-benefit location-allocation John Fortney
model for public facilities: an econometric approach
Geographical Analysis
Vol. 28, No. 1, 1996, pp. 67-92 This research develops and operationalizes a facility location-allocation model based on cost-benefit principles derived from welfare economics. Despiote the theoretical advantages of cost-benefit location-allocation models, the difficulties associated with estimating household preferences for public facilities have heretofore prevented their application. This research demonstrates that the hedonicpricing methodology can be effectively used to estimate preferences for public facilities. Specifically, household preferences for Baltimore public middle schools were estimated from the spatial variation in housing prices using the random bidding model. To provide an example of the methodology, the cost-benefit location-allocation objective function was maximized to simultaneously determine the optimal number, quality, and locations of Baltimore middle schools. The cost-benefit approach to facility location constitutes a major improvement over existing methods because it directly incorporates user preferences into the objective function and because the number and quality of facilities can be determined endogenously rather than being specified as a constraint a priori.
Weber problems with alternative transportation
systems
Emilio Carrizosa, Antonio M. Rodriguez-Chia European Journal of Operational Research
Vol. 97, No. 1, 1997, pp. 87-93 In this paper we address a planar p-facility location problem where, together with a metric induced by a gauge, there exists a series of rapid transit lines, which can be used as alternative transportation system to reduce the total transportation cost. The location problem is reduced to solving a finite number of (multi)-Weber problems, from which localization results are obtained. In particular, it is shown that, if the gauge in use is polyhedral, then the problem is reduced to finding ap-median.
Heuristic concentration: two stage solution construction
K. E. Rosing and C. S. ReVelle European Journal of Operational Research
Vol. 97, No. 1, 1997, pp. 75-86 By utilizing information
from multiple runs of an interchange heuristic we construct a new solution that is generally better than the best local optimum previously found. This new, two stage, approach to combinatorial optimization is demonstrated in the context of the p-median problem. Two layers of optimization are superimposed. The first layer is a conventional heuristic the second is a heuristic or exact procedure which draws on the concentrated solution set generated by the initial heuristic. The intention is to provide an alternative heuristic procedure which, when dealing with large problems, has a higher probability of producing optimal solutions than existing methods. The procedure is fairly general and appears to be applicable to combinatorial problems in a number of contexts.
198
Locating vehicle inspection stations to protect a transportation
network
M. John Hodgson, Kenneth E. Rosing and Jianjun Zhang Geographical Analysis Vol. 28, No. 4, 1996, pp. 299-314
We develop a new conceptual
approach to locating inspection stations for hazardous vehicles,
prevention, and compare it to the previous, punitive, philosophy of the flow-capturing location model.
We implement this preventive protection philosophy with a new mixed integer program that maximizes hazard avoidance by locating a number of inspection stations to detect and remove hazardous vehicles as early in their trips as possible. We test the model’s performance and analyze the spatial characteristics of solutions simulating several potential applications. Our computations demonstrate that a relaxed integer-linear program is overly demanding computationally and that a simple greedy heuristic lacks robustness. We suggest further approaches to developing more powerful and efficient solution methods.
A computational
method for market area analysis on a network
Atsuyuki Okabe and Masayuki Kitamura Geographical Analysis
Vol. 28, No. 4, 1996, pp. 330-349 This paper shows a computational method for market area analysis assuming that stores and consumers are distributed over a network and the distance between two points on the network is given by the route distance. First, we consider five basic questions often raised in market area analysis, and show a general method, called the network transformation method, that gives an intuitive way of looking at computational methods for solving these questions. Second, assuming that consumers follow the Huff model, we consider four questions concerning market area delineation and market potential often discussed in market area analysis in practice. We show that the network transformation method is also useful to develop computational methods for solving these questions. One of the notable results is that market area delineation of the Huff model (which is analytically difficult to obtain on a plane) can be exactly obtained on a network.
Using simple genetic algorithms to calibrate spatial interaction models G. Diplock and S. Openshaw Geographical Analysis Vol. 28, No. 3, 1996, pp. 262-279
The paper investigates the use of two genetic algorithms in an attempt to obtain globally optimal parameter estimates for a mix of simple and complex spatial interaction models. The genetic algorithms work well and are strongly advocated as a more robust approach particularly for use with the more complex multiparameter models where the differences in both performance and parameter values are judged to be significant.
An efficient search strategy for site-selection decisions in an expert system Theo A. Arentze, Aloys W. J. Borgers and Harry J. P. Timmermans Geographical Analysis
Vol. 28, No. 2, 1996, pp. 126-146 This paper describes an algorithm for spatial search, which is used in an expert system for site selection. The algorithm, named ProfMat, is able to find the best site in the area of interest even when the number of possible sites is large and many decision criteria are involved. Compared to commonly used search procedures, ProfMat improves the efficiency of spatial search in two ways. First, the best site is identified through an iterative rather than a linear process of selection and
Abstracts in Location Science
199
evaluation of optional sites. Second, an area is searched by narrowing down the focus to increasingly smaller areas and, thus, sites are evaluated as much as possible groupwise. The ProfMat procedure is illustrated by analyzing the problem of retail site selection. A comparison with alternative search procedures shows that ProfMat considerably reduces the evaluation costs needed to find the best site. The implementation of the algorithm in an expert system shows how ProfMat can be used in combination with specialist’s knowledge to solve site-selection problems. The efficiency of the procedure allows considering large sets of optinoal sites, so that it may improve the quality of the outcome.
A cost-benefit location-allocation John Fortney
model for public facilities: an econometric approach
Geographical Analysis
Vol. 28, No. 1, 1996, pp. 67-92 This research develops and operationalizes a facility location-allocation model based on cost-benefit principles derived from welfare economics. Despiote the theoretical advantages of cost-benefit location-allocation models, the difficulties associated with estimating household preferences for public facilities have heretofore prevented their application. This research demonstrates that the hedonicpricing methodology can be effectively used to estimate preferences for public facilities. Specifically, household preferences for Baltimore public middle schools were estimated from the spatial variation in housing prices using the random bidding model. To provide an example of the methodology, the cost-benefit location-allocation objective function was maximized to simultaneously determine the optimal number, quality, and locations of Baltimore middle schools. The cost-benefit approach to facility location constitutes a major improvement over existing methods because it directly incorporates user preferences into the objective function and because the number and quality of facilities can be determined endogenously rather than being specified as a constraint a priori.
Weber problems with alternative transportation
systems
Emilio Carrizosa, Antonio M. Rodriguez-Chia European Journal of Operational Research
Vol. 97, No. 1, 1997, pp. 87-93 In this paper we address a planar p-facility location problem where, together with a metric induced by a gauge, there exists a series of rapid transit lines, which can be used as alternative transportation system to reduce the total transportation cost. The location problem is reduced to solving a finite number of (multi)-Weber problems, from which localization results are obtained. In particular, it is shown that, if the gauge in use is polyhedral, then the problem is reduced to finding ap-median.
Heuristic concentration: two stage solution construction
K. E. Rosing and C. S. ReVelle European Journal of Operational Research
Vol. 97, No. 1, 1997, pp. 75-86 By utilizing information
from multiple runs of an interchange heuristic we construct a new solution that is generally better than the best local optimum previously found. This new, two stage, approach to combinatorial optimization is demonstrated in the context of the p-median problem. Two layers of optimization are superimposed. The first layer is a conventional heuristic the second is a heuristic or exact procedure which draws on the concentrated solution set generated by the initial heuristic. The intention is to provide an alternative heuristic procedure which, when dealing with large problems, has a higher probability of producing optimal solutions than existing methods. The procedure is fairly general and appears to be applicable to combinatorial problems in a number of contexts.