Design of a Distribution Network in a Multi-product, Multi-period Green Supply Chain System Under Demand Uncertainty

Azam Boskabadi , Mirpouya Mirmozaffari , Reza Yazdani , Ali Farahani
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引用次数: 24

Abstract

This paper proposes a novel fuzzy mathematical model for a distribution network design problem in a multi-product, multi-period, multi-echelon, multi-plant, multi-retailer, multi-mode of transportation green supply chain system. The three purposes of the model are to minimise total network cost, maximise net profit per capita for each human resource, and diminish CO2 emission throughout the network. P-hub median location with multiple allocations is used for locating the distribution centres. One scenario is designed for fuzzy customer demands with a trapezoidal membership function. Furthermore, the model determines the design of the network (selecting the optimum numbers, locations of plants, and distribution centres to open), finding the best strategy for material transportation through the network with the availability of different transportation modes, the capacities level of the facilities (plants or distribution centres (DCs)), and the number of outsourced products. Finally, all uncertain customer demands for all product types can be satisfied based on the methods mentioned above. This multi-objective mixed-integer non-linear mathematical model is solved by NSGA-II, MOPSO and a hybrid meta-heuristic algorithm. The results show that NSGA-II is the exclusive algorithm that obtains the best result according to the evaluation criteria.

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需求不确定性下多产品、多周期绿色供应链系统配电网设计
针对多产品、多周期、多梯次、多工厂、多零售商、多运输方式的绿色供应链系统中的配送网络设计问题,提出了一种新的模糊数学模型。该模型的三个目的是最小化总网络成本,最大化每个人力资源的人均净利润,以及减少整个网络的二氧化碳排放。使用多重分配的P-hub中位数定位来定位配送中心。针对模糊客户需求,设计了一种梯形隶属函数方案。此外,该模型确定了网络的设计(选择最优的数量、工厂的位置和要开放的配送中心),通过不同运输模式的可用性、设施(工厂或配送中心(dc))的能力水平和外包产品的数量,找到通过网络进行物资运输的最佳策略。最后,基于上述方法可以满足所有产品类型的所有不确定客户需求。采用NSGA-II、MOPSO和混合元启发式算法求解该多目标混合整数非线性数学模型。结果表明,根据评价标准,NSGA-II是获得最佳结果的唯一算法。
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