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A multiobjective memetic algorithm for integrated process planning and scheduling problem in distributed heterogeneous manufacturing systems

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Abstract

With the deepening of economic globalization and the development of the manufacturing industry, distributed manufacturing patterns have become a popular topic in current production research. In the background of distributed shop scheduling, process planning problems in different factories are considered integrally with scheduling problems to utilize the heterogeneous machining resources of distributed factories. To address actual production problems more concretely, this paper investigates the multiobjective distributed integrated process planning and scheduling (MODIPPS) problem to minimize makespan, maximum machine load, and total machine load, and it establishes a mixed-integer linear programming (MILP) model. In addition, by designing a new encoding method based on the OR-nodes of the process network graph, this paper proposes a multiobjective memetic algorithm (MOMA) to solve the problem. The proposed MOMA can guarantee the feasibility of individuals by several specially designed genetic operators so that the process precedence constraints in the network graph are satisfied in the whole algorithm period. Furthermore, the algorithm introduces a simulated annealing (SA) mechanism to avoid falling into a local optimum by accepting relatively poor individuals with a certain probability. Finally, through comparison experiments on benchmarks, the proposed method shows sufficient effectiveness and superiority in solving MODIPPS problems compared with existing classic multiobjective optimization algorithms.

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Acknowledgements

This work is supported in part by the National Key R&D Program of China under Grant No. 2019YFB1704600, in part by the National Natural Science Foundation of China under Grant Nos. 51825502 and U21B2029, and in part by the Program for HUST Academic Frontier Youth Team under Grant 2017QYTD04.

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Authors and Affiliations

  1. State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

    Qihao Liu, Xinyu Li, Liang Gao & Guangchen Wang

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  1. Qihao Liu
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  2. Xinyu Li
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  3. Liang Gao
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  4. Guangchen Wang
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Correspondence to Xinyu Li.

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Qihao Liu, Xinyu Li, Liang Gao declare that they have no conflict of interest or financial conflicts to disclose.

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Liu, Q., Li, X., Gao, L. et al. A multiobjective memetic algorithm for integrated process planning and scheduling problem in distributed heterogeneous manufacturing systems. Memetic Comp. 14, 193–209 (2022). https://doi.org/10.1007/s12293-022-00364-x

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