Paper Info
Title
A location-allocation heuristic for the capacitated multi-facility Weber problem with probabilistic customer locations
Abstract
The capacitated multi-facility Weber problem is concerned with locating m facilities in the Euclidean plane, and allocating their capacities to n customers at minimum total cost. The deterministic version of the problem, which assumes that customer locations and demands are known with certainty, is a non-convex optimization problem and difficult to solve. In this work, we focus on a probabilistic extension and consider the situation where the customer locations are randomly distributed according to a bivariate distribution. We first present a mathematical programming formulation, which is even more difficult than its deterministic version. We then propose an alternate location–allocation local search heuristic generalizing the ideas used originally for the deterministic problem. In its original form, the applicability of the heuristic depends on the calculation of the expected distances between the facilities and customers, which can be done for only very few distance and probability density function combinations. We therefore propose approximation methods which make the method applicable for any distance function and bivariate location distribution.
Year
DOI
Venue
2009
10.1016/j.ejor.2008.10.014
European Journal of Operational Research
Keywords
Field
DocType
Heuristics,Expected distance,Facility location–allocation,Probabilistic capacitated Weber problem
Mathematical optimization,Heuristic,Joint probability distribution,Location-allocation,Facility location problem,Probabilistic logic,Local search (optimization),Optimization problem,Mathematics,Weber problem
Journal
Volume
Issue
ISSN
198
3
0377-2217
Citations 
PageRank 
References 
8
0.56
10
Authors
4
Name
Order
Citations
PageRank
I. Kuban Altinel115014.60
Engin Durmaz2121.02
Necati Aras346230.62
Kerem Can Özkisacik480.90