A decomposition based memetic algorithm for multi-objective vehicle routing problem with time windows |
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| Affiliation: | 1. School of Computer Science and Technology, Xidian University, Xi׳an, China;2. School of Software, Xidian University, Xi׳an, China;3. School of Computer Science and Information Technology, RMIT University, Melbourne, Australia;1. Technical University of Crete, School of Production Engineering and Management, Decision Support Systems Laboratory, University Campus, 73100 Chania, Greece;2. Technical University of Crete, School of Production Engineering and Management, Computational Mechanics and Optimization Laboratory, 73100 Chania, Greece;1. Department of Information, Logistics and Innovation, VU University Amsterdam, The Netherlands;2. Black School of Business, Penn State Erie, The Behrend College, Erie, PA 16563, United States;3. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong;1. CORMSIS and Southampton Business School, University of Southampton, Southampton SO17 1BJ, United Kingdom;2. CIRRELT and HEC Montréal, 3000, chemin de la Côte-Sainte-Catherine, Montréal, Canada H3T 2A7;3. CIRRELT and Canada Research Chair in Distribution Management, HEC Montréal, 3000, chemin de la Côte-Sainte-Catherine, Montréal, Canada H3T 2A7;1. School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA;2. School of Management, Université du Québec à Montréal, Montreal, QC, Canada;3. MAGI, École Polytechnique, Montreal, QC, Canada;4. CIRRELT, C.P. 8888, succ. Centre-ville, Montreal, QC H3C 3P8, Canada;1. School of Computer and Information, Anqing Normal University, Anqing 246133, China;2. School of Engineering and Computer Science, Victoria University of Wellington, Kelburn 6012, New Zealand;3. USTC-Birmingham Joint Research Institute in Intelligent Computation and its Applications (UBRI), School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China |
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| Abstract: | ![]()
Multi-objective evolutionary algorithm based on decomposition (MOEA/D) provides an excellent algorithmic framework for solving multi-objective optimization problems. It decomposes a target problem into a set of scalar sub-problems and optimizes them simultaneously. Due to its simplicity and outstanding performance, MOEA/D has been widely studied and applied. However, for solving the multi-objective vehicle routing problem with time windows (MO-VRPTW), MOEA/D faces a difficulty that many sub-problems have duplicated best solutions. It is well-known that MO-VRPTW is a challenging problem and has very few Pareto optimal solutions. To address this problem, a novel selection operator is designed in this work to enhance the original MOEA/D for dealing with MO-VRPTW. Moreover, three local search methods are introduced into the enhanced algorithm. Experimental results indicate that the proposed algorithm can obtain highly competitive results on Solomon׳s benchmark problems. Especially for instances with long time windows, the proposed algorithm can obtain more diverse set of non-dominated solutions than the other algorithms. The effectiveness of the proposed selection operator is also demonstrated by further analysis. |
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| Keywords: | Multi-objective optimization Memetic algorithm Decomposition Vehicle routing problem with time windows |
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