Scenario-Based Multi-Objective Location-Routing Model for Pre-Disaster Planning: A Philippine Case Study

Maria Rossana D. de Veluz (), Anak Agung Ngurah Perwira Redi, Renato R. Maaliw, Satria Fadil Persada, Yogi Tri Prasetyo and Michael Nayat Young
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Maria Rossana D. de Veluz: School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
Anak Agung Ngurah Perwira Redi: Industrial Engineering Department, Faculty of Engineering and Technology, Sampoerna University, Jakarta 12780, Indonesia
Renato R. Maaliw: College of Engineering, Southern Luzon State University, Lucban 4328, Philippines
Satria Fadil Persada: BINUS Business School Undergraduate Program, Entrepreneurship Department, Bina Nusantara University, Malang 65154, Indonesia
Yogi Tri Prasetyo: International Bachelor Program in Engineering, Yuan Ze University, 135 Yuan-Tung Roa-Chung-Li, Taoyuan City 32003, Taiwan
Michael Nayat Young: School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines

Sustainability, 2023, vol. 15, issue 6, 1-33

Abstract: The demand for humanitarian supply chains grows daily as the incidence of calamities rises. Typhoons cause thousands of casualties each year. As a result, policymakers and governmental authorities must develop effective readiness and response measures as part of pre-disaster plans. This paper proposed a stochastic model for multi-objective location-routing for creating a humanitarian network for pre-disaster response. The model aims to minimize the overall costs of the network’s setup, the time required to travel through it, and the number of vehicles necessary for transferring affected individuals to evacuation centers. The model concentrates on pre-disaster scenarios in uncertainty. The provided model was implemented in an actual scenario in one of the Philippines’ provinces and solved using Multi-Objective Particle Swarm Optimization (MOPSO), which is also contrasted with Multi-Objective Simulated Annealing (MOSA) and the ε-constraint approach. According to empirical findings, the model can be used to identify distribution hubs and evacuation centers and choose the best routes in unexpected and actual disaster scenarios. Given that the ideal number, location, and capacity of DCs and ECs are known in advance, government decision-makers can solve any potential shortages and problems during the disaster.

Keywords: multi-objective optimization; humanitarian supply chain; MOPSO; pre-disaster planning; scenario (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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