A multi-vessel quay crane assignment and scheduling problem: Formulation and heuristic solution approach |
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| Affiliation: | 1. Department of Electronics Convergence Engineering, Wonkwang University, 344-2, Shinyong-Dong, Iksan, Jeonbuk 570-749, South Korea;2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2G7, Canada;3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland;1. Department of Electrical and Computer Engineering, University of Macau, Avenida Padre Tomas Pereira, Taipa, Macau;2. Department of Computer Science, Huizhou University, Huizhou 516007, China;1. Department of Management and Marketing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;2. Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;1. Liaoning Key Laboratory of Manufacturing System and Logistics, The Logistics Institute, Northeastern University, Shenyang 110819, China;2. School of Business and Economics, Loughborough University, Leicestershire LE11 3TU, UK;1. Transport and Mobility Laboratory, École Polytechnique Fédérale de Lausanne, Switzerland;2. Department of Civil Engineering, National University of Singapore, Singapore;3. The Logistics Institute – Asia Pacific, National University of Singapore, Singapore |
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| Abstract: | This paper presents a new approach to analyze the integrated quay crane assignment and scheduling problem (QCASP). The problem determines the assignment of quay cranes to vessels and the sequence of tasks to be processed by each quay crane simultaneously, and accounts for important considerations such as safety margins between quay cranes (QCs), ordering conditions and vessel priority. Furthermore, QCs can travel from one vessel to another vessel whenever tasks are complete. The integrated problem is difficult to solve with exact methods due to its complexity. Therefore, a genetic algorithm (GA) is proposed to solve the integrated QCASP. Computational results validate the performance of the proposed GA. |
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| Keywords: | Quay crane assignment Quay crane scheduling Genetic algorithms Integrated models |
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