Solving the uncapacitated multi-facility Weber problem by vector quantization and self-organizing maps

Solving the uncapacitated multi-facility Weber problem by vector quantization and self-organizing maps

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Article ID: iaor20072044
Country: United Kingdom
Volume: 57
Issue: 1
Start Page Number: 82
End Page Number: 93
Publication Date: Jan 2006
Journal: Journal of the Operational Research Society
Authors: , ,
Keywords: heuristics, optimization, location
Abstract:

The uncapacitated multi-facility Weber problem is concerned with locating m facilities in the Euclidean plane and allocating the demands of n customers to these facilities with the minimum total transportation cost. This is a non-convex optimization problem and difficult to solve exactly. As a consequence, efficient and accurate heuristic solution procedures are needed. The problem has different types based on the distance function used to model the distance between the facilities and customers. We concentrate on the rectilinear and Euclidean problems and propose new vector quantization and self-organizing map algorithms. They incorporate the properties of the distance function to their update rules, which makes them different from the existing two neural network methods that use rather ad hoc squared Euclidean metric in their updates even though the problem is originally stated in terms of the rectilinear and Euclidean distances. Computational results on benchmark instances indicate that the new methods are better than the existing ones, both in terms of the solution quality and computation time.

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