Dynamic Evolution Analysis of ITIO Based on Transport Flexibility and Limited Rationality

Fuchang Li
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Abstract

One of the most common problems in supply chain management is minimizing transportation and inventory costs. Inventory and transportation are the two main components of logistical costs, which account for the majority of an enterprise's logistical expenses. Inventory-Transportation Integrated Optimization (ITIO) is concerned with the distribution of a single product from a single facility (depot) to a set of geographically dispersed customers over a given planning horizon. In this paper, we develop degenerative earning matrixes under bounded rationality in accordance with the characteristics of an ITIO problem in a "many to many" distribution system, gain replicator dynamics of the two sides and solve the ESS. First, we describe the problem of ITIO. Second, this paper presents the ITIO model which considers the transport flexibility. Third, we analyze the replicator dynamics and evolutionary stability analysis of ITIO. Forth, this paper gives computational results to validate the thesis conclusions. And then concludes the paper with some remarks. This study concluded that the choices of retailers with bounded rationality depend on the choices of suppliers with perfect rationality. The conclusion states that the ESS of a retailer with bounded rationality and imperfect information is the same as a retailer with perfect rationality and perfect information.
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基于运输灵活性和有限理性的ITIO动态演化分析
供应链管理中最常见的问题之一是最小化运输和库存成本。库存和运输是物流成本的两个主要组成部分,占企业物流费用的大部分。库存-运输集成优化(ITIO)关注的是在给定的规划范围内,将单个产品从单个设施(仓库)分发到一组地理上分散的客户。本文根据“多对多”分配系统中ITIO问题的特点,建立了有限理性下的退化学习矩阵,获得了双方的复制因子动力学,并求解了ESS。首先,我们描述ITIO问题。其次,提出了考虑传输灵活性的ITIO模型。第三,分析了ITIO的复制因子动力学和进化稳定性分析。第四,给出了计算结果来验证本文的结论。最后对全文作了总结。研究发现,具有有限理性的零售商的选择依赖于具有完全理性的供应商的选择。结论表明,具有有限理性和不完全信息的零售商的ESS与具有完全理性和完全信息的零售商的ESS相同。
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