Modeling and Solving the Open Location-Allocation-Routing Problem with Split Delivey under Demand Uncertainty and Customer Satisfaction in Crisis Conditions

Document Type : Original Article

Author
Esfandyar Ataei
Assistant Professor, Department of Industrial Engineering, Payame Noor University, Tehran, Iran
10.22034/road.2026.588064.2509
Abstract
Effective solutions for the open location-allocation-routing problem in relief distribution during crises are of great importance for logistics companies and governmental agencies.Therefore, rapid response to needs and the delivery of required items to affected areas are of very high priority due to the uncertainty in the severity of the crisis and the number of affected regions.This research investigates the multi-objective modeling of open location-allocation-routing in relief distribution with split deliveries after an earthquake in District1ofTehran.The aim is to optimally determine the locations of relief centers, routing, and optimal allocation of the relief fleet,considering uncertainty in relief demand,arrival time to target points, relief fleet capacity,time windows and customer satisfaction in post-earthquake conditions.In this paper, a multi-objective model is considered with the objectives of minimizing costs,response time and increasing customer satisfaction.Given the NP-hard nature of problem, the proposed mathematical model was implemented using the e-constraint method with CPLEX 10.1software for small and medium sized instances, and two algorithms the Non-dominated Sorting Genetic Algorithm and the Multi-Objective Grey Wolf Optimizer were used for large-scale instances and their performance was compared with each other based on solution improvement.The results the superiority of the NSGA-II algorithm over theMOGWO algorithm, meaning that in most test problems, the NSGA-II algorithm provides better solutions in a shorter time.The results also show that considering the assumption of split delivery of customer demands leads to a reduction in the final cost, and with an increase in demand, the number of established distribution centers increases.
Keywords
Routing
Location
Non-dominated Sorting Genetic Algorithm
Customer Satisfaction
Time Window
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