A Genetic Algorithm for Integrated Scheduling of Container Handing Systems at Container Terminals from a Low-Carbon Operations Perspective

Yan Zheng, Meixian Xu, Zhaohu Wang () and Yujie Xiao ()
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Yan Zheng: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Meixian Xu: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Zhaohu Wang: School of Marketing and Logistics Management, Nanjing University of Finance and Economics, Nanjing 210046, China
Yujie Xiao: Business School, Nanjing University, Nanjing 210093, China

Sustainability, 2023, vol. 15, issue 7, 1-21

Abstract: At container terminals, quay cranes, yard trucks, and yard cranes are mainly used to transfer containers. Driven by the demand for a green and low-carbon economy, an integrated scheduling problem considering three types of handling equipment of container handling systems is studied. As the task of transferring each container is completed by the three handling equipment sequentially, the optimal solution may not be found by only studying one type of equipment separately from a green operations perspective. The inter-dependency of different equipment should be considered to guarantee the overall performance of container handling systems with low-carbon operations so as to reduce energy consumption. In this paper, this integrated problem is formulated as a mixed integer linear programming (MILP). Since the MILP cannot be applied to solve large-sized practical problems, a genetic algorithm (GA) is developed. In the proposed GA, a three-dimension chromosome representation is proposed, which integrates the coordination of three handling equipment. A new mechanism including three pairs of crossover and mutation is used in parallel in GA with the aim of enhancing the efficiency of searching for good solutions. Each pair of crossover and mutation is specific to one dimension of a solution. Moreover, a novel heuristic mutation is developed to diversify solutions. The computational results indicate that the developed solution method for the integrated scheduling problem is promising and the heuristic mutation can highly improve the solution quality.

Keywords: integrated scheduling; low-carbon; container handling systems; mixed integer linear programming; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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