Qin Jin, Xiang Hui, Ye Yong, Ni Linglin
School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China.
School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China ; School of Traffic and Transportation Engineering, Changsha University of Science & Technology, Changsha 410076, China.
ScientificWorldJournal. 2015;2015:826363. doi: 10.1155/2015/826363. Epub 2015 Mar 5.
A stochastic multiproduct capacitated facility location problem involving a single supplier and multiple customers is investigated. Due to the stochastic demands, a reasonable amount of safety stock must be kept in the facilities to achieve suitable service levels, which results in increased inventory cost. Based on the assumption of normal distributed for all the stochastic demands, a nonlinear mixed-integer programming model is proposed, whose objective is to minimize the total cost, including transportation cost, inventory cost, operation cost, and setup cost. A combined simulated annealing (CSA) algorithm is presented to solve the model, in which the outer layer subalgorithm optimizes the facility location decision and the inner layer subalgorithm optimizes the demand allocation based on the determined facility location decision. The results obtained with this approach shown that the CSA is a robust and practical approach for solving a multiple product problem, which generates the suboptimal facility location decision and inventory policies. Meanwhile, we also found that the transportation cost and the demand deviation have the strongest influence on the optimal decision compared to the others.
研究了一个涉及单一供应商和多个客户的随机多产品容量设施选址问题。由于需求的随机性，必须在设施中保持合理数量的安全库存以实现适当的服务水平，这导致库存成本增加。基于所有随机需求服从正态分布的假设，提出了一个非线性混合整数规划模型，其目标是最小化总成本，包括运输成本、库存成本、运营成本和设置成本。提出了一种组合模拟退火（CSA）算法来求解该模型，其中外层子算法优化设施选址决策，内层子算法基于确定的设施选址决策优化需求分配。用这种方法得到的结果表明，CSA是一种求解多产品问题的稳健且实用的方法，它生成次优的设施选址决策和库存策略。同时，我们还发现，与其他因素相比，运输成本和需求偏差对最优决策的影响最强。
