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Liner shipping network design with emission control areas: A genetic algorithm-based approach
Institution:1. Centre of Excellence in Supply Chain Innovation and Transportation (CESIT), Kedge Business School, 680 Cours de la Libération, 33400 Talence, France;2. Sustainable Engineering Asset Management (SEAM) Research Group, Research Institute of Sciences & Engineering and Industrial Engineering and Engineering Management Department, College of Engineering, University of Sharjah, 27272 Sharjah, United Arab Emirates;3. University of Carthage, National Engineering School of Carthage, UR-OASIS-ENIT, Tunis, Tunisia;4. Sustainable Engineering Asset Management (SEAM) Research Group, Research Institute of Sciences & Engineering, University of Sharjah, 27272 Sharjah, United Arab Emirates;1. Strome College of Business, Old Dominion University, Norfolk, VA 23529, USA;2. Institute of Transport Studies, Department of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia;3. Department of Civil and Environmental Engineering, National University of Singapore, Singapore 117576, Singapore;1. Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim, Norway;2. Norwegian Marine Technology Research Institute (MARINTEK), Trondheim, Norway;3. Department of Transport, Technical University of Denmark, Lyngby, Denmark;1. Department of Maritime and Transport Technology, Delft University of Technology, Delft, The Netherlands;2. School of Navigation, Wuhan University of Technology, Hubei, China;3. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hong Kong;4. Hubei Key Laboratory of Inland Shipping Technology, China;1. Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, Trondheim, Norway;2. Norwegian Marine Technology Research Institute (MARINTEK), Trondheim, Norway;3. Department of Transport, Technical University of Denmark, Lyngby, Denmark
Abstract:To curb emissions, containerized shipping lines face the traditional trade-off between cost and emissions (CO2 and SOx) reduction. This paper considers this element in the context of liner service design and proposes a mixed integer linear programming (MILP) model based on a multi-commodity pickup and delivery arc-flow formulation. The objective is to maximize the profit by selecting the ports to be visited, the sequence of port visit, the cargo flows between ports, as well as the number/operating speeds of vessels on each arc of the selected route. The problem also considers that Emission Control Areas (ECAs) exist in the liner network and accounts for the vessel carrying capacity. In addition to using the MILP solver of CPLEX, we develop in the paper a specific genetic algorithm (GA) based heuristic and show that it gives the possibility to reach an optimal solution when solving large size instances.
Keywords:Liner service  Optimum speed  Arc-flow formulation  Mixed integer linear programming (MILP)  Genetic algorithms (GA)
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