Genetic Algorithm Approach for Inventory and Supply Chain Management

Poonam Mishra
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Abstract

Inventory and supply chain management is a real concern for business community in today's globally competitive scenario. Various inventory models are proposed, significant parameters are analysed and finally optimized by researchers in order to give managers an insight for the different parameters. Mathematical and logical analysis of different inventory and supply chain models helps mangers in overall cost reduction and further higher revenue generation. Members often encounter conflicting interest and unforeseen scenario. So, all this make supply chain very complex and dynamic process. Complex and uncertain nature of inventory and supply chain, many times either it is not feasible to solve the issue with traditional methods or it is not cost effective. Thus many researchers are using artificial intelligence approach for investigation. Genetic algorithm is one among them that works efficiently with complex nature of the inventory and supply chain management. This article provides an up to date review about the role of GA in overall inventory and supply chain management.
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库存与供应链管理的遗传算法
库存和供应链管理是当今全球竞争环境下商界真正关注的问题。研究人员提出了各种库存模型,并对重要参数进行了分析和优化,以使管理者对不同的参数有更深入的了解。对不同库存和供应链模型的数学和逻辑分析有助于管理者降低总体成本,进一步提高收入。成员经常会遇到利益冲突和不可预见的情况。因此,所有这些使得供应链非常复杂和动态的过程。库存和供应链的复杂性和不确定性,很多时候不是用传统的方法解决问题是不可行的,就是不符合成本效益。因此,许多研究人员正在使用人工智能方法进行研究。遗传算法是其中一种能够有效解决库存和供应链管理复杂性问题的算法。本文对遗传算法在整体库存和供应链管理中的作用进行了最新的综述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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