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Journal of System Simulation

Abstract

Abstract: For the problem of multi-objective integrated process planning and scheduling (MOIPPS), an improved hybrid optimization algorithm considering global and local optimum is proposed to optimize two objectives about minimum makespan and energy consumption. A multi-objective problem model and solution framework are established by analyzing the difference and connection between process planning and scheduling in integrated system. A hybrid optimization algorithm is proposed for the two-stage integration problem. In the process planning stage, global search algorithm is employed to provide a variety of process schemes for the integrated system and to ensure the global search performance of the integrated algorithm. With regard to the scheduling stage, an improved tabu search algorithm is proposed, of which, crossover and random sampling operator is aimed at expanding the solution searching region and neighborhood tabu search is promoting the algorithm to converge instantly respectively. Pareto non-dominated sorting is employed to acquire the global optimal solution. Through contrastive analysis on diverse experiment results, the efficiency and consistency of the proposed algorithm is verified in solving multi-objective integrated process planning and scheduling problems.

First Page

1197

Last Page

1209

CLC

TP391.9

Recommended Citation

Gu Wenbin, Qing Jiexia, Fang Jie, et al. Improved Hybrid Optimization Algorithm for Multi-objective IPPS Problem[J]. Journal of System Simulation, 2025, 37(5): 1197-1209.

DOI

10.16182/j.issn1004731x.joss.24-0031

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