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作 者:温海骏[1,2] 刘明周[1] 刘长义[1] 刘从虎[1]
机构地区:[1]中北大学机械与动力工程学院,山西太原030051 [2]合肥工业大学机械与汽车工程学院,安徽合肥230009
出 处:《计算机集成制造系统》2016年第2期529-537,共9页Computer Integrated Manufacturing Systems
基 金:国家973计划资助项目(2011CB013406)~~
摘 要:针对多品种发动机再制造生产过程中存在的不确定性因素,以最小化生产成本为目标,基于可信性理论建立了不确定环境下汽车发动机两阶段模糊再制造生产计划模型。该模型考虑多品种产品回收情况下,拆解零件的再制造加工数量、加工成本、新零件采购数量以及市场需求的不确定性对再制造加工生产计划的影响,将生产过程分为两个阶段,并采用补偿函数逼近方法,将具有无限支撑的无限维优化模型转化为有限维优化问题进行求解,设计了基于逼近方法的粒子群算法来求解两阶段模糊生产计划问题。以曲轴飞轮总成为仿真实例,验证了该混合智能优化算法解决两阶段模糊规划问题的有效性和合理性。For uncertainty factors existed in remanufacturing process of multi-item automobile engine,a two-stage fuzzy production planning model was constructed under uncertain environment based on credibility theory with the goal of minimizing the production cost.By considering the influences of remanufacturing machining quantity,machining cost,new purchase cost and market demand's uncertainty on remanufacturing production plan under the case of multi-item products recovery,the production process was divided into two stages,and the optimization model of infinite dimensional was transformed into a finite dimensional optimization problem by adopting the method of compensation function approximation.A hybrid particle swarm optimization algorithm based on approximation method was designed to solve the two-stage fuzzy production planning problems.A simulation case of crankshaft flywheel assembly was provided to validate the efficiency and rationality of the proposed approach.
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