Many-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logistics

Article Many-Objective Simulation Optimization for Camp Location Problems in Humanitarian Logistics Yani Xue 1,*, Miqing Li 2, Hamid Arabnejad 1, Diana Suleimenova 1, Alireza Jahani 1, Bernhard C. Geiger 3, Freek Boesjes 4, Anastasia Anagnostou 1, Simon J.E. Taylor 1, Xiaohui Liu 1, and Derek Groen 1,* 1 Department of Computer Science, Brunel University London, Uxbridge, United Kingdom 2 School of Computer Science, University of Birmingham, Birmingham, United Kingdom 3 Know-Center GmbH, Graz, Austria 4 Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands * Correspondence: Yani Xue ([email protected]); Derek Groen ([email protected]) Received: 10 March 2024 Accepted: 19 August 2024 Published: 26 September 2024 Abstract: Humanitarian organizations face a rising number of people fleeing violence or persecution, people who need their protection and support. When this support is given in the right locations, it can be timely, effective and cost-efficient. Successful refugee settlement planning not only considers the support needs of displaced people, but also local environmental conditions and available resources for ensuring survival and health. It is indeed very challenging to find optimal locations for establishing a new refugee camp that satisfy all these objectives. In this paper, we present a novel formulation of the facility location problem with a simulation-based evolutionary many-objective optimization approach to address this problem. We show how this approach, applied to migration simulations, can inform camp selection decisions by demonstrating it for a recent conflict in South Sudan. Our approach may be applicable to diverse humanitarian contexts, and the experimental results have shown it is capable of providing a set of solutions that effectively balance up to five objectives.