首页> 外文期刊>RAIRO operations research >A NEW MODEL FOR LOGISTICS AND TRANSPORTATION OF FASHION GOODS IN THE PRESENCE OF STOCHASTIC MARKET DEMANDS CONSIDERING RESTRICTED RETAILERS CAPACITY
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A NEW MODEL FOR LOGISTICS AND TRANSPORTATION OF FASHION GOODS IN THE PRESENCE OF STOCHASTIC MARKET DEMANDS CONSIDERING RESTRICTED RETAILERS CAPACITY

机译:考虑受限制零售商能力的随机市场需求存在的新型物流与运输新型号

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摘要

In today's world, using fashion goods is a vital of human. In this research, we focused on developing a scheduling method for distributing and selling fashion goods in a multi-market/multi-retailer supply chain while the product demands in markets are stochastic. For this purpose, a new multi-objective mathematical programming model is developed where maximizing the profit of selling fashion goods and minimizing delivering time and customer's dissatisfaction are considered as objective functions. In continue due to the complexity of the problem, a number of metaheuristics are compared and a hybrid of Non-dominated Sorting Genetic Algorithm II (NSGAII) and simulated annealing is selected for solving the case studies. Then, in order to find the best values for input parameters of the algorithm, a Taguchi method is applied. In continue, a number of case studies are selected from literature review and solved by the algorithm. The outcomes are analyzed and it is found that using multi-objective models can find more realistic solutions. Then, the model is applied for a case study with real data from industry and outcomes showed that the proposed algorithm can be successfully applied in practice.
机译:在今天的世界里,使用时尚商品是一种重要的人。在这项研究中,我们专注于开发在多市场/多零售商供应链中分配和销售时尚商品的调度方法,而市场上的产品需求是随机的。为此,开发了一种新的多目标数学规划模型,在最大化销售时尚商品的利润和最小化提供时间和客户的不满,被视为客观职能。继续由于问题的复杂性,比较了许多成分训练,并且选择了非主导的分类遗传算法II(NSGaii)和模拟退火的混合用于解决案例研究。然后,为了找到算法的输入参数的最佳值,应用了TAGUCHI方法。继续,从文献综述中选择许多案例研究并由算法解决。分析结果,发现使用多目标模型可以找到更现实的解决方案。然后,该模型应用于来自行业的真实数据的案例研究,结果表明,所提出的算法可以在实践中成功应用。

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