The distribution processing and replenishment policy of the supply chain under asymmetric information and deterioration: Insight into the information value

This paper proposes a dynamic lot-sizing problem for the supply chain, based on the fuzzy theory. Past studies on inventory problems of asymmetric information typically focus on suppliers providing incentive contracts to attract buyers to cooperate with the replenishment policy, and the uncertain environment is constructed by statistics and probability methods. However, random variables are difficult to calculate during the analysis process. This paper focuses on analyzing how asymmetric information will affect cost deviation. The analytical result can be an important basis for decision makers when deciding budget for gaining insight into the information. This proposed problem considers the fact products deteriorate before distribution processing. In this problem, asymmetric information is constructed, using fuzzy theory. Suppliers may be responsible for monitoring the cost, to gain insight into the information. However, if the investment budget is larger than the cost deviation caused by the asymmetric information, it is not worthwhile. Decision makers must understand the degree of cost deviation caused by asymmetric information. This paper proposes some properties and theorems of the proposed problem. This paper applies those proposed properties to reduce the solution space for the algorithm to search. An ant colony optimization is constructed to solve this problem, based on the theorem of this paper. Numerical analysis shows variables related to asymmetric information affect cost deviation.