Solution methods for a min-max facility location problem with regional customers considering closest Euclidean distances

2020-03-01
DOLU HASTÜRK, NAZLI
HASTÜRK, UMUR
Tural, Mustafa Kemal
We study a facility location problem where a single facility serves multiple customers each represented by a (possibly non-convex) region in the plane. The aim of the problem is to locate a single facility in the plane so that the maximum of the closest Euclidean distances between the facility and the customer regions is minimized. Assuming that each customer region is mixed-integer second order cone representable, we firstly give a mixed-integer second order cone programming formulation of the problem. Secondly, we consider a solution method based on the Minkowski sums of sets. Both of these solution methods are extended to the constrained case in which the facility is to be located on a (possibly non-convex) subset of the plane. Finally, these two methods are compared in terms of solution quality and time with extensive computational experiments.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS

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Citation Formats
N. DOLU HASTÜRK, U. HASTÜRK, and M. K. Tural, “Solution methods for a min-max facility location problem with regional customers considering closest Euclidean distances,” COMPUTATIONAL OPTIMIZATION AND APPLICATIONS, pp. 537–560, 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/38619.