Activities involving transformation of raw materials, various resources and components into final products and also delivering it to the end customer incur a significant cost during the selection of location of a warehouse that can be easily accessed by various actors of the supply chain. To minimize upstream and downstream transportation costs, the center of gravity (CoG) analysis method is used to find the potential warehouse locations for a given demand network which have an impact on the entire supply chain network. Mixed Integer Linear Programming (MILP), an open source tool is developed for implementing CoG method along with certain service level constraints to find optimal potential locations with the least cost. In this paper, an optimization tool has been designed for a forward logistics network with several novel methods like Customer Location Selection (CLS), Customer Packets along with other business heuristics that optimize and enhance the existing MILP to get the optimal solutions with low computational cost and runtime. Finally, recommending an alternative network of facilities which reduces overall costs compared to the existing network. An user interface has also been developed to make a user friendly interaction with the model. We can conclude that this model can significantly help companies reduce costs during the logistics network design.

翻译：为尽量减少上游和下游运输费用,使用重力中心分析方法为特定需求网络寻找潜在的仓库地点,对整个供应链网络产生影响。混合整形线性规划(MILP)开发了一个开放源码工具,用于实施CoG方法,同时使用某些服务层面的制约因素,以找到成本最低的最佳潜在地点。在本文中,设计了一个优化工具,用于前方后勤网络,采用几种新颖方法,如客户地点选择(CLS)、客户包裹和其他商业超常方法,优化和加强现有的MILP,以获得最佳解决方案,低计算成本和运行时间。最后,建议建立一个替代设施网络,降低与现有网络相比的总体成本。还开发了一个用户界面,以便与模型进行方便用户的互动。我们可以得出结论,这一模型可以极大地帮助公司降低物流网络设计过程中的成本。