GENETIC ALGORITHM FOR OBSTACLE LOCATION-ALLOCATION PROBLEMS WITH CUSTOMER

Document Type

Article

Publication Title

Journal of Industrial and Management Optimization

Publication Date

7-1-2021

Abstract

In this paper we propose a metaheuristic approach to solve a customer priority based location-allocation problem in presence of obstacles and location-dependent supplier capacities. In many network optimization problems presence of obstacles prohibits feasibility of a regular network design. This includes a wide range of applications including disaster relief and pandemic disease containment problems in healthcare management. We focus on this application since fast and efficient allocation of suppliers to demand nodes is a critical process that impacts the results of the containment strategy. In this study, we propose an integrated mixed-integer program with location-based capacity decisions that considers customer priorities in the network design. We propose an efficient multi-stage genetic algorithm that solves the problem in continuous space. The computational findings show the best allocation strategies derived from proposed algorithms.

Volume

17

Issue

4

First Page

1753

Last Page

1769

DOI

10.3934/jimo.2020044

ISSN

15475816

E-ISSN

1553166X

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