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Reducing truck emissions at container terminals in a low carbon economy: Proposal of a queueing-based bi-objective model for optimizing truck arrival pattern
Institution:1. School of Management, Shanghai University, Shanghai, China;2. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Hong Kong;3. Department of Industrial and Systems Engineering, National University of Singapore, Singapore;4. Logistics Research Center, Shanghai Maritime University, Shanghai, China;1. School of Economics & Management, Tongji University, Shanghai 200092, P.R. China;2. Department of Industrial Engineering & Logistics Management, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong;3. School of data & computer science, Sun Yat-sen University, Gangzhou 510275, P.R. China;4. Laboratoire Génie Industriel, Centrale Supélec, Université Paris-Saclay, Grande Voie des Vignes, 92290 Châtenay-Malabry, France
Abstract:This study proposes a methodology to optimize truck arrival patterns to reduce emissions from idling truck engines at marine container terminals. A bi-objective model is developed minimizing both truck waiting times and truck arrival pattern change. The truck waiting time is estimated via a queueing network. Based on the waiting time, truck idling emissions are estimated. The proposed methodology is evaluated with a case study, where truck arrival rates vary over time. We propose a Genetic Algorithm based heuristic to solve the resulting problem. Result shows that, a small shift of truck arrivals can significantly reduce truck emissions, especially at the gate.
Keywords:Container terminal  Truck emissions  Bi-objective optimization  Queueing network  Fluid based approximation
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