基于改进粒子群优化算法的混流装配线演进平衡

发布时间：2018-12-08 11:03

【摘要】：随着产品需求的多样化、装配工艺及技术进步、设备更新等动态变化,装配线平衡方案需不断调整,甚至重新规划与演进平衡。为了探究上述因素对混流装配线演进平衡的影响,提出了实现装配线演进平衡的方法,建立了以最小化装配线的生产节拍、站间平滑指数、演进平衡调整成本为优化目标的混流装配线演进平衡数学模型,并通过改进粒子群优化算法进行优化。在该算法中,为增加粒子的多样性和搜索能力,克服传统粒子群优化算法快速收敛等问题,以粒子进化的成功率来更新算法中的惯性因子,将群体中非最优粒子中的有利信息迁移到群体中的最优粒子上,从而加快算法的搜索速度。结合某企业的生产实例验证了该方法的有效性和可行性。
[Abstract]:With the diversification of product demand, the development of assembly process and technology, and the dynamic change of equipment renewal, the balance scheme of assembly line needs to be adjusted constantly, and even the balance between replanning and evolution needs to be rearranged. In order to explore the influence of the above factors on the balance of mixed flow assembly line evolution, the method of realizing the balance of assembly line evolution is put forward, and the production rhythm and the smoothness index between stations are established to minimize the production rhythm of assembly line. The mathematical model of evolutional equilibrium of mixed-flow assembly line with adjusting cost as optimization objective is optimized by improved particle swarm optimization (PSO) algorithm. In order to increase the diversity and search ability of particles and overcome the problems of fast convergence of traditional particle swarm optimization (PSO) algorithm, the inertia factor of the algorithm is updated with the success rate of particle evolution. In order to speed up the search speed, the favorable information from the non-optimal particles in the population is transferred to the optimal particles in the population. The effectiveness and feasibility of this method are verified by a production example of an enterprise.
【作者单位】：贵州大学现代制造技术教育部重点实验室;
【基金】：国家自然科学基金资助项目(51505094) 贵州省科学技术基金计划资助项目(黔科合基础(2016)1037) 贵州省应用基础研究计划重大资助项目(黔科合JZ字(2014)2001) 贵州大学引进人才科研资助项目[贵大人基合字(2014)60号]~~
【分类号】：F425;F274;TP18

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