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Journal of System Simulation

Abstract

Abstract: Aiming at the joint optimization problem of energy-saving distributed manufacturing and preventive maintenance for semiconductor wafers, a two-stage green scheduling model considering both the manufacturing stage and the inspection and repair stage is established to minimize the makespan, the total carbon emissions and the total preventive maintenance cost. An improved hybrid multi-objective grey wolf optimization (IHMGWO)algorithm is proposed. The decoding schemes of factory allocation strategy, machine allocation strategy and synchronous scheduling maintenance strategy considering the flexibility of maintenance workers are designed in IHMGWO. By designing the initial population fusion strategy, predation behavior search strategy, and sub-population mutation strategy, the optimization performance of the algorithm is improved. The comparative experiments of 360 test cases show that the IHMGWO algorithm proposed in this paper can achieve most dominance for SP indicator and all dominance for IGD and Ω indicator, which has certain advantages and competitiveness for solving such problems.

First Page

584

Revised Date

2021-05-06

Last Page

602

CLC

TP301.6

Recommended Citation

Jun Dong, Chunming Ye. Research on Joint Optimization of Energy-Saving Distributed Manufacturing and Preventive Maintenance for Semiconductor Wafers[J]. Journal of System Simulation, 2022, 34(3): 584-602.

Corresponding Author

Chunming Ye,yechm6464@163.com

DOI

10.16182/j.issn1004731x.joss.21-0190

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