This article presents the case of a food grain distribution organization in India and explores the inventory and warehouse parameters that are relevant in regional level allocation of food grain rakes. Three penalty factors namely rake penalty factor, capacity utilization penalty factor and weekly penalty factor are defined to represent the parameters identified. The article formulates a constraint programming model to minimize the sum of the three penalty factors, named total penalty. A tailor-made heuristic is designed to solve the model and a webserver-based Decision Support System (DSS) is also developed using the heuristic for rake allocation planning. The proposed heuristic is tested via computational experiments using historical data collected from the organization. The rake allocation plans generated by the heuristic are found to have lower total penalty value than the historical plans prepared by the organization. This establishes the superiority and applicability of the proposed heuristic based planning methodology.

本文介绍了印度一家粮食分销组织的案例，并探讨了与区域一级粮食耙分配相关的库存和仓库参数。定义了三个惩罚因子，即耙式惩罚因子、产能利用率惩罚因子和周惩罚因子来表示识别的参数。文章制定了一个约束规划模型，以最小化三个惩罚因素的总和，称为总惩罚。设计了一个量身定制的启发式算法来解决该模型，并且还使用启发式算法开发了基于网络服务器的决策支持系统 (DSS) 用于 rake 分配规划。使用从组织收集的历史数据，通过计算实验对所提出的启发式方法进行测试。发现启发式生成的 rake 分配计划的总惩罚值低于组织准备的历史计划。这确立了所提出的基于启发式的规划方法的优越性和适用性。