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为了解决传统配送中心选址没有同时考虑库存持有成本和决策环境的动态变化的问题,建立了一种新的模型。首先,利用两步骤近似方法获得(Q,R)库存策略下每一个周期配送中心的库存成本计算公式;然后,针对传统设施动态选址模型对选址成本的不恰当表示进行了修正,并与库存成本计算方法相结合,从而建立考虑库存成本的配送中心动态选址模型。最后,分别用遗传算法、克隆选择算法、粒子群优化算法求解所建立的模型,并从算法的精确度、稳定性、运算速度和收敛性比较了三种算法的性能。算例测试结果表明:所建立的模型是有效的;从总体上看,遗传算法的适应性要强于克隆选择算法和粒子群算法。
In order to solve the problem that the location of traditional distribution center does not take into account the dynamic changes of inventory holding cost and decision environment at the same time, a new model is established. First of all, the inventory cost formula of each cycle distribution center under (Q, R) inventory strategy is obtained by two-step approximation method. Then, the improper representation of site cost is modified according to the traditional facility dynamic location model, Inventory cost calculation method to establish a distribution center to consider the cost of inventory dynamic location model. Finally, the genetic algorithm, the clonal selection algorithm and the particle swarm optimization algorithm are respectively used to solve the established model. The performances of the three algorithms are compared from the accuracy, stability, speed and convergence of the algorithm. The results of the example test show that the established model is effective. Generally speaking, the genetic algorithm is more adaptive than the clonal selection algorithm and the particle swarm optimization algorithm.