Solving a Stochastic Multi-Objective Location-Routing Problem: a Comparative Study of Meta-heuristics
Publish Year: 1403
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICIORS17_189
تاریخ نمایه سازی: 5 شهریور 1403
Abstract:
This paper presents a multi-objective location-routing problem with capacitated vehicles to reduce the total cost of the system. The model considers times of traveling, service and waiting by vehicles while guarantees the least probability that the sum of these parameters be lower than a predetermined value when minimization of this value is considered as an objective function. Due to NP-hardness of the model, we propose a multi-objective imperialist competitive algorithm (MOICA) to solve the given problem. The great efficiency of the proposed MOICA is demonstrated via comparing with two famous meta-heuristics, named Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and Pareto archived evolution strategy (PAES). After adjustment several crossover and mutation strategies for each algorithm based on response surface methodology, the associated results in terms of four existing comparison metrics on several benchmark instances indicate that the proposed MOICA outperforms the others
Keywords:
Location-routing problem (LRP) , Facility location , Vehicle routing , imperialist competitive algorithm (ICA) , Linearization
Authors
Amir-Mohammad Golmohammadi
Department of Industrial Engineering, Arak University, Arak
Hamidreza Abedsoltan
School of Industrial Engineering, College of Engineering, University of Tehran
Negin Esmaeelpour
School of Industrial Engineering, College of Engineering, University of Tehran