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Multicriteria planar location problems
68
Abstracts
in Location
Analysis
The queueing maximal availability location problem: a model for the siting of emergency vehicles Vladimir Marianov and Charles ReVeIle European Journal of Operational Research Vol. 93, 1996, pp. 110-120 The maximal availability location (MALP) has been recently formulated as a probabilistic version of the maximal covering location problem. The added feature in MALP is that randomness onto the availability of servers is considered. In MALP, though, it is assumed that the probabilities of different servers being busy are independent. In this paper, we utilize results from queueing theory to relax this assumption, obtaining a more realistic model for emergency systems: the queueing MALP or QMALP. We also consider in this model that travel times or distance along arcs of the network are random variables. We show here how to site limited numbers of emergency vehicles, such as ambulances, in such a way as to maximize the calls for service which have an ambulance available within a time or distance standard with reliability cc-using a queueing theory model for server availability. We also propose some extensions to the basic model. Formulations are presented and computational experience is offered. Massively parallel analog tabu search using neural networks applied to simple plant location problems Shivakumar Vaithyanathan, Laura I. Burke and Michael A. Magent European Journal of Operational Research Vol. 93, 1996, pp. 317-330 Neural networks and tabu search are two very significant techniques which have emerged recently for the solution of discrete optimization problems. Neural networks possess the desirable quality of implementability in massively parallel hardware while the tabu search metaheuristic shows great promise as a powerful global search method. Tabu neural network (TANN) integrates an analog version of the short term memory component of tabu search with neural networks to generate a massively parallel, analog global search strategy that is hardware implementable. In TANN, both the choice of the element to enter the tabu list as well as the maintenance of the decision elements in tabu status is accomplished via neuronal activities. In this paper we apply TANN to the simple plant location problem. Comparisons with the Hopfield-Tank network show an average improvement of about 85% in the quality of solutions obtained. Multicriteria planar location problems H. W. Hamacher and S. Nickel European Journal of Operational Research Vol. 94, 1996, pp. 66-86 Given Q different objective functions, three types of single-facility problems are considered: lexicographic, pareto and max ordering problems. After discussing the interrelation between the problem types, a complete characterization of lexicographic locations and some instances of pareto and max ordering locations is given. The characterizations result in efficient solution algorithms for finding these locations. The paper relies heavily on the theory of restricted locations developed by the same authors, and can be further extended, for instance, to multi-facility problems with several objectives. The proposed approach is more general than previously published results on multicriteria planar location problems and is particularly suited for modelling real-world problems. Tight linear programming relaxation of uncapacitated p-hub median problems Darko Skorin-Kapov, Jadranka Skorin-Kapov and Morton O’Kelly European Journal of Operational Research Vol. 94, 1996, pp. 582-593 The problem of locating hub facilities and allocating non-hub nodes to those hubs arises frequently in the design of communication networks, airline passsenger flow and parcel delivery networks. In this paper we consider uncapacitated multiple and single allocation p-hub median problems. We develop
Abstracts
in Location
Analysis
The queueing maximal availability location problem: a model for the siting of emergency vehicles Vladimir Marianov and Charles ReVeIle European Journal of Operational Research Vol. 93, 1996, pp. 110-120 The maximal availability location (MALP) has been recently formulated as a probabilistic version of the maximal covering location problem. The added feature in MALP is that randomness onto the availability of servers is considered. In MALP, though, it is assumed that the probabilities of different servers being busy are independent. In this paper, we utilize results from queueing theory to relax this assumption, obtaining a more realistic model for emergency systems: the queueing MALP or QMALP. We also consider in this model that travel times or distance along arcs of the network are random variables. We show here how to site limited numbers of emergency vehicles, such as ambulances, in such a way as to maximize the calls for service which have an ambulance available within a time or distance standard with reliability cc-using a queueing theory model for server availability. We also propose some extensions to the basic model. Formulations are presented and computational experience is offered. Massively parallel analog tabu search using neural networks applied to simple plant location problems Shivakumar Vaithyanathan, Laura I. Burke and Michael A. Magent European Journal of Operational Research Vol. 93, 1996, pp. 317-330 Neural networks and tabu search are two very significant techniques which have emerged recently for the solution of discrete optimization problems. Neural networks possess the desirable quality of implementability in massively parallel hardware while the tabu search metaheuristic shows great promise as a powerful global search method. Tabu neural network (TANN) integrates an analog version of the short term memory component of tabu search with neural networks to generate a massively parallel, analog global search strategy that is hardware implementable. In TANN, both the choice of the element to enter the tabu list as well as the maintenance of the decision elements in tabu status is accomplished via neuronal activities. In this paper we apply TANN to the simple plant location problem. Comparisons with the Hopfield-Tank network show an average improvement of about 85% in the quality of solutions obtained. Multicriteria planar location problems H. W. Hamacher and S. Nickel European Journal of Operational Research Vol. 94, 1996, pp. 66-86 Given Q different objective functions, three types of single-facility problems are considered: lexicographic, pareto and max ordering problems. After discussing the interrelation between the problem types, a complete characterization of lexicographic locations and some instances of pareto and max ordering locations is given. The characterizations result in efficient solution algorithms for finding these locations. The paper relies heavily on the theory of restricted locations developed by the same authors, and can be further extended, for instance, to multi-facility problems with several objectives. The proposed approach is more general than previously published results on multicriteria planar location problems and is particularly suited for modelling real-world problems. Tight linear programming relaxation of uncapacitated p-hub median problems Darko Skorin-Kapov, Jadranka Skorin-Kapov and Morton O’Kelly European Journal of Operational Research Vol. 94, 1996, pp. 582-593 The problem of locating hub facilities and allocating non-hub nodes to those hubs arises frequently in the design of communication networks, airline passsenger flow and parcel delivery networks. In this paper we consider uncapacitated multiple and single allocation p-hub median problems. We develop