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基于NSPSO算法的混合裝配線平衡問題多目標(biāo)優(yōu)化
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國家自然科學(xué)基金資助項(xiàng)目(51175304)


Multi-objective Optimization of Mixed Assembly Lines Balancing Problem Based on Non-dominated Sorting Particle Swarm Optimization
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    摘要:

    不同品種作業(yè)元素的作業(yè)時(shí)間差異經(jīng)常引起混合品種裝配線的工作站瞬時(shí)負(fù)荷瓶頸問題,依據(jù)給定的排產(chǎn)順序,,兼顧裝配線平均負(fù)荷和瞬時(shí)負(fù)荷,,考慮不同品種作業(yè)元素的作業(yè)時(shí)間差異對(duì)裝配線平衡的影響,,建立了以最小化工作站內(nèi)裝配時(shí)間波動(dòng),、工作站負(fù)荷平滑指數(shù)及裝配線超載時(shí)間為目標(biāo)的混合品種裝配線平衡模型,,并設(shè)計(jì)了基于非支配排序的粒子群優(yōu)化算法(NSPSO),。實(shí)例驗(yàn)證表明,,基于非支配排序的粒子群算法在求解大規(guī)模混合品種平衡問題方面比遺傳算法具有更高的求解質(zhì)量和求解效率,。

    Abstract:

    The station instantaneous workload bottleneck was caused by task processing time differences among different models. According to the given production schedule and considering the average workload and instantaneous load of assembly line, mixed assembly line balancing model was built with the objective of minimum station processing time variation, station’s workload smooth index and assembly line overload time. The effect of task processing time differences among different models on the assembly line balance was also taken in to account. The multi-objective optimization algorithm based on non-dominated sorting particle swarm optimization (NSPSO) was designed. The example verified that, compared with genetic algorithm, NSPSO had higher solution quality and solving efficiency in large mixed balancing problem. 

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李智,姜兆亮,劉文平.基于NSPSO算法的混合裝配線平衡問題多目標(biāo)優(yōu)化[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2013,44(10):248-252. Li Zhi, Jiang Zhaoliang, Liu Wenping. Multi-objective Optimization of Mixed Assembly Lines Balancing Problem Based on Non-dominated Sorting Particle Swarm Optimization[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(10):248-252.

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  • 在線發(fā)布日期: 2013-10-14
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