Comparative solution approach with quadratic and genetic programming to multi-objective healthcare facility location problem

Abstract

Facility layout planning is an indispensable part of the manufacturing and service operations. In the literature, there are two main different approaches for the solution of facility layout problem: While the first one aims to minimize both total transportation and assignment costs in a quantitative way, the second one aims to maximize the closeness relationship in a more qualitative way. In this study, we use both of these approaches to model a multi-objective facility layout optimization problem depending on a Quadratic Assignment Problem (QAP) formulation. We consider three objective which are minimizing the total walking distance, and the maximization of area satisfaction level and closeness relationships. Since these objectives have different scales, we normalize them to prevent a potential domination effect. Then, we solve the problem using Quadratic Assignment Problem (QAP) formulation and a genetic algorithm approach and compare the results. These approaches provide non-dominated solutions to multi-objective problem being considered. In this way, we assign the departments of a healthcare facility to predetermined areas. In addition, our formulation enables the planners to prevent patient losses and increase the patient satisfaction.