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机构地区:[1]青岛大学复杂性科学研究所,山东青岛266071
出 处:《青岛大学学报(工程技术版)》2015年第4期105-109,共5页Journal of Qingdao University(Engineering & Technology Edition)
基 金:山东省自然科学基金资助项目(ZR2010GM006)
摘 要:针对整车装配企业入厂物流中短驳合并运输问题,本文将短驳合并运输抽象成多产品单供应商单目的地的联合补货问题,并以短驳合并运输的总成本最小为目标,在采用间接组合的策略下,建立数学优化模型,并利用粒子群算法求解,同时,以某汽车制造厂的入厂物流为例进行仿真实验。仿真结果表明,与决策变量相关的可变供应成本的平均最优解为2 189 070,比文献[2]中两种算法求得的结果分别降低了5.2%和0.2%;与决策变量相关的可变供应成本最优解为2 165 700元,比文献[2]中BFD启发式算法降低6.2%,比文献[2]中的整数箱子编码的组群遗传算法降低1.3%。说明间接组合策略比直接组合策略更能有效降低供应成本,体现了该模型的优越性。该研究对大型装配企业入厂物流活动的组织优化具有一定的参考意义。The problem of short split merged transportation problems about inbound logistics of vehicle assembly plants is studied in this paper. It is abstracted as a joint replenishment problem of multiple products, single supplier and single destination. Indirect grouping strategy is used to establish a mathematical model which aims at the minimum total cost of the short split merged transportation. It is solved by using particle swarm optimization. The inbound logistics of an automotive assembly plant is used as an example for simulation study. The simulation results show that the average optimal solution of variable costs of supply which is related to decision variables is 2 189 070, and it has respectively reduced 5.2% and 0.2% compared with both algorithms in literature [2]. The optimal solution of variable costs of supply which is related to decision variables is 2 165 700, it has reduced 6.2% compared with the heuristic algorithm based on the BFD in literature [2], it has reduced 1.3 %0 compared with the grouping genetic algorithm based on the idea of integer coding in literature [2]. The results show that the indirect grouping strategy can be more effective in reducing the supply cost compared with the direct grouping strategy, and it reflects the superiority of the model. The study has guiding significance for the organization optimization problem about inbound logistics of large assembly plants.
分 类 号:F426.4[经济管理—产业经济] TP18[自动化与计算机技术—控制理论与控制工程]
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