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首页> 美国卫生研究院文献>The Scientific World Journal >A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand
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A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand

机译：具有随机需求的多产品容量工厂定位的模拟退火方法

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摘要

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.
机译：研究了涉及一个供应商和多个客户的随机多产品容量设施定位问题。由于随机需求，必须在设施中保留一定数量的安全库存以达到合适的服务水平，从而导致库存成本增加。基于所有随机需求的正态分布假设，提出了一种非线性混合整数规划模型，其目标是使总成本最小化，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算法（CSA）来求解该模型，其中外层子算法优化设施选址决策，内层子算法根据确定的设施选址决策优化需求分配。通过这种方法获得的结果表明，CSA是解决多种产品问题的可靠且实用的方法，它会产生次优的设施位置决策和库存策略。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大。

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