Metaheuristic Approaches to Facility Location Problems: A Systematic Review

Abstract

Facility Location Problems (FLPs) aim to determine the most suitable location for the desired facility given the problem constraints. The sheer variety of facility types in the modern era has made the task of facility location management too complex for manual selection and its associated demand allocation. That gave rise to this literature, which consists of AI-based and non-AI-based approaches at solving different FLPs. In this research paper, we analyze the surveys in the literature, before funneling down to systematically and comprehensively survey the papers utilizing AI-based approaches. We present statistics and related insights of the facility industries, the type of constraints used in the problem, the prominent parameters characterizing how the problem was formulated, and whether the proposed solution is evolutionary. Additionally, we investigate the performance of the solutions and their justified methodology. Finally, we discuss the benefits and drawbacks of the most commonly used AI algorithms used in the literature. We conclude with gaps for further research potential identified in the literature.