GENETIC ALGORITHM FOR OBSTACLE LOCATION-ALLOCATION PROBLEMS WITH CUSTOMER

1Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Priorities, Ayough, A., Farhadi, F., Zandieh, M., & Rastkhadiv, P. (2021). GENETIC ALGORITHM FOR OBSTACLE LOCATION-ALLOCATION PROBLEMS WITH CUSTOMER. Journal of Industrial and Management Optimization, 17(4), 1753–1769. https://doi.org/10.3934/jimo.2020044

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free