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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Mutual adjustment search with incentive for supply chain planning coordination
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Mutual adjustment search with incentive for supply chain planning coordination

机译：相互调整搜索，促进供应链计划协调

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摘要

Supply chains are complex systems, which include several independent organisations with different objectives. A key issue in supply chain management is the coordination of supply chain planning decisions. Supply chain planning systems introduced in the literature can be classified into two main planning systems: centralised and decentralised planning systems. Centralised systems can theoretically optimise supply chain performance, although its implementation requires a high degree of information exchange among supply chain partners. This leads to difficulties when independent partners do not want to share information. In order to address these difficulties, decentralised systems are designed for supply chains where each member is a separate economic entity that makes its operational decisions independently, yet with some minimal level of information sharing. In this paper, we propose a decentralised coordination mechanism based on a negotiation-like mutual adjustment of planning decisions, rooted in mathematical programming. This mechanism, unlike traditional centralised system, involves two enterprises, which interact with each other in order to improve their individual and collective performance. Computational analysis shows that the proposed negotiation-like coordination mechanism leads to near-optimal results when compared to central coordination, while maintaining fairness in terms of revenue sharing.
机译：供应链是复杂的系统，其中包括几个具有不同目标的独立组织。供应链管理中的关键问题是供应链计划决策的协调。文献中介绍的供应链计划系统可以分为两个主要计划系统：集中式和分散式计划系统。尽管集中化系统的实施需要在供应链合作伙伴之间进行高度的信息交换，但从理论上讲它可以优化供应链绩效。当独立合作伙伴不想共享信息时，这会导致困难。为了解决这些困难，分散式系统专为供应链而设计，其中每个成员都是一个独立的经济实体，可以独立地制定其运营决策，但信息共享水平最低。在本文中，我们提出了一种基于协调性的，基于规划决策的协商式相互调整的分散式协调机制，该机制扎根于数学编程中。与传统的集中式系统不同，此机制涉及两个企业，它们彼此交互以提高其个人和集体绩效。计算分析表明，与集中式协调相比，拟议的类似协商的协调机制可导致近乎最佳的结果，同时在收益共享方面保持公平。

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