Abstract
In this paper, we focus on the two crossover automated stacking cranes (ASCs) scheduling problem that arises at a storage block in an automated container terminal. To address relocation during retrieval operations, we use two methods with job precedence constraints: (1) adjusting the operation sequence of jobs to avoid relocation operations and (2) optimizing the dispatching for relocation operations to improve the efficiency of ASCs. Therefore, the method proposed in this paper optimizes the dispatching for storage, retrieval, and relocation and the routes of the ASCs while considering interferences between the ASCs and job precedence constraints. A branch-and-cut algorithm based on the characteristics of the problem is designed to decompose the problem into two problem classes connected via logic-based Benders constraints. Numerical experiments indicate that the proposed algorithm is efficient for solving realistically sized problems. Furthermore, the influence of the number of relocations is investigated based on experimental results.








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Funding
This work is supported by the National Natural Science Foundation of China (Grant Nos. 71372086, 71831002), Program for Innovative Research Team in University of Ministry of Education of China (Grant Nos. IRT_17R13), and the Fundamental Research Funds for the Central Universities (Grant Nos. 3132019501, 3132019502).
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The contribution of this paper is twofold: (1) The practical factors including relocation operations and interference are simultaneously considered in the scheduling of two crossover ASCs. Relocation operations are addressed by adjusting the operation sequence to reduce relocations and optimizing the dispatching for unavoidable relocation jobs. (2) We design a logic-based Benders decomposition algorithm within a branch-and-cut framework to obtain an optimal ASC schedule. The algorithm can effectively solve real-world problems and can be implemented in practical scheduling.
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Chen, S., Zeng, Q. & Hu, Y. Scheduling optimization for two crossover automated stacking cranes considering relocation. Oper Res Int J 22, 2099–2120 (2022). https://doi.org/10.1007/s12351-020-00601-6
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DOI: https://doi.org/10.1007/s12351-020-00601-6