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Journal of System Simulation

Abstract

Abstract: Aiming at the problem of unbalanced running load caused by idle or blocked workstations in the assembly line of mixed-flow hydraulic pump, a hybrid genetic tabu search algorithm solution and computer simulation verification method are proposed. A hybrid genetic tabu search algorithm with strong local search capability is designed with the optimization objectives of minimizing the production beats of the mixed-flow assembly line, the operational loads distributed among different workstations and the operational load smoothing indices of different products within the same workstation. The algorithm incorporates multi-fragment crossover and fragmentation of feasible solutions through Hamming distance mutation operations. The optimal combination of parameters for the algorithm is determined using the orthogonal experiment method. The effectiveness and superiority of the hybrid genetic forbidden search algorithm are verified using both the classical case set and the hydraulic pump assembly line. The start-up sequencing scheme is simulated using Plant Simulation software to analyze the equipment situation of the hydraulic pump assembly line based on actual production. The research findings demonstrate that the optimization method effectively had reduced production beat and smoothing index of the mixed-flow assembly line. It also balances the workload of different products between workstations and within the same workstation, thus achieving a balanced re-optimization of the mixed-flow assembly line.

First Page

167

Last Page

182

CLC

TP391.9

Recommended Citation

Wang Ke, Guan Sijia, Yin Xiyan, et al. Research on Mixed-model Assembly Line Balancing Optimization Based on Hybrid Genetic Tabu Search Algorithm[J]. Journal of System Simulation, 2025, 37(1): 167-182.

Corresponding Author

Yin Xiyan

DOI

10.16182/j.issn1004731x.joss.23-1045

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