Location Science最新文献

We consider the absolute p-center problem on a general network and propose a spanning tree approach which is motivated by the fact that the problem is NP-hard on general networks but solvable in polynomial time on trees. We first prove that every connected network possesses a spanning tree whose p-center solution is also a solution for the network under consideration. Then we propose two classes of spanning trees that are shortest path trees rooted at certain points of the network. We give an experimental study, based on 1440 instances, to test how often these classes of trees include an optimizing tree. We report our computational results on the performance of both types of trees.

In this paper we propose a flexible new model for the location of competitive facilities that may derive their demand for service from both special-purpose purchase trips by their customers and from “intercepting” customers passing by a facility while en route to another destination on the network. Our model combines the features of the spatial interaction and flow interception models. An efficient heuristic procedure is developed, with worst case analysis provided. We also develop a tight upper bound and a branch-and-bound scheme for our model. Results of a set of computational experiments are presented.

Presented here is the axiomatic foundation of a model-generating framework for formulating location–allocation models in the field of integrated regional solid waste management. Data requirements are standardized, a generalized network objective function is developed and a set of potential constraint menu is compiled. Along the framework development, many local peculiarities are considered; resulting mixed-integer, linear models are solvable by exact or heuristic algorithms. These models are adaptable to each criterion of a customized set, thus supporting multicriterial analysis.

In a dynamically changing network, the costs or distances between locations are changing in each discrete time period. We consider the location of emergency facilities that must minimize the maximum distance to any customer on the network across all time periods. We call the problem of locating p centers over k underlying networks corresponding to k periods the k-Network p-Center problem. The problem is considered when, in each period, the network satisfies the triangle inequality. In this paper, we provide a polynomial time 3-approximation algorithm for Δ k-Network p-Center for the case k=2. We discuss generalizations inspired by this problem to other optimization problems with multiple underlying networks and the objective of finding a single solution that varies as little as possible from the optimum for each network. The additional combinatorial problems discussed include: sorting; perfect matching; shortest path; minimum spanning tree; and minimum cut. All are shown to be NP-hard for k⩾2.

The concentrator location problem (CLP) is a classical problem in the network design literature. Given a set of candidate locations and the concentrator capacities, the problem is to answer the following related questions. How many concentrators should be used? Where should they be located? Which users are to be assigned to each concentrator? A Lagrangian relaxation is used to obtain lower bounds for this problem. The Lagrangian relaxation is complemented by a tabu search (TS) metaheuristic. Computational results are given for a set of randomly generated problems and for test problems available in the literature. The tabu search heuristic (TSH) is shown to be competitive with other solution procedures available for the problem.