A Review of Advances in Multi-objective Optimization for Facility Location Problems

Facility location problems play a vital role in transportation, healthcare, humanitarian logistics, and sustainable mobility, requiring a careful balance between efficiency, equity, and environmental sustainability. This article conducts a structured comparative review of ten representative studies to synthesize advancements in multi-objective optimization for facility location problems, rather than a full systematic literature review. The literature is categorized into five domains: hub location issues, emergency medical services, humanitarian and disaster logistics, electric vehicle infrastructure, and methodological advances in decision-support innovations, providing a focused synthesis of methodological and thematic progress in the field. A comparative analysis demonstrates a range of methodologies, including mathematical programming and metaheuristics to simulation-based and interactive optimization approaches, each addressing trade-offs among cost, accessibility, robustness, and fairness. Themes include the prevalence of multi-objective trade-offs, necessity for uncertainty management, integration of infrastructure and service provision, and increasing significance of equality considerations. Persistent research gaps such as limited scalability, lack of dynamic adaptation, insufficient stakeholder integration, incomplete sustainability metrics, and the need for hybrid optimization with machine learning are identified as key directions for future work. By bridging application-driven studies with methodological advances, this review provides an integrated perspective to guide both researchers and practitioners toward resilient, human-centered facility location strategies.