A multiobjective optimization approach for location‐allocation of clinics

Abstract

In order to establish new healthcare facilities, their optimal number and locations should be determined. Unsuitable locations for these facilities may result in substandard customer services and increased expenses. To solve this location‐allocation problem, this study applied a multiobjective model that combined geographical information system (GIS) analysis with a multiobjective genetic algorithm. Optimum sites for new clinics were determined by considering four objectives: minimizing total travel cost, minimizing inequity in access to clinics, minimizing the land‐use incompatibility in the study area, and minimizing the costs of land acquisition and facility establishment. Chromosomes of varying lengths were used in the multiobjective optimization process. An important advantage of this is that multiple optimal solutions with different numbers of healthcare facilities can be compared directly. An a posteriori preference method was used in this study. TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) was applied to assess and compare the Pareto‐optimal solutions and to select the best solution according to different weight vectors. Visualization of the best solution according to each weight vector and compromising among different objectives provided valuable possibilities for selection of the best alternative to decision makers.

Solving the bi‐objective capacitated p‐median problem with multilevel capacities using compromise programming and VNS

“…Some approaches can be used to solve multiobjective or bi‐objective problems. Beheshtifar and Alimoahmmadi () integrated geographical information system analysis with a genetic algorithm to locate optimum sites of new clinics using multiobjective criteria. Rath et al.…”

Geographical Information Systems and Multicriteria Decisions Integration Approach for Hospital Location Selection

“…7,[35][36][37] Multi-objective optimization with genetic algorithm and integration with GIS is also new topic being studied by researchers. 38 MCE and GIS abilities can also be integrated. In the existing literature, this integration is known as \multi-criteria spatial decision-making" or \spatial multi-criteria decision-making".…”

“…41 In spite of popularity of multicriteria spatial approaches in location analysis in energy related facilities consideration, [42][43][44][45][46][47] hospital location selection problem has not been much investigated for location allocation of healthcare facilities. 38 For other GIS and multi-criteria integration studies see Refs. 48-58. To measure the convenience levels of the hospital alternatives, GIS' analytic functions can be used to create input data for multi-criteria approaches.…”

Integrated optimization model for distribution network design: a case study of the clothing industry

“…The model determines the number and locations of the facilities to be opened, and assigns the demand points to these facilities. Beheshtifar and Alimoahmmadi (2014) proposed a multiobjective optimization approach for location-allocation of clinics. Meier (2017) presented an improved mixed-integer program for hub location problems with a stepwise cost function.…”