A Paper B2C Multi-item Replenishment Anddelivery Coordination Problem With Fuzzy Random Demands

In recent years,with the rapid development of the e-commerce,the online shopping lifestyle have become a part of Chinese people's life.B2 C e-commerce has a wide coverage of multi-products and whole-category products,and the uncertainty of multi-product demand has gradually become a core problem that harass the B2 C e-commerce supply chain.B2 C e-commerce companies gradually focuse on the replenishment-delivery coordination.However,the differentiation of the customer demand and the uncertainty of the commodity demand have not only caused the inconsistency between the procurement and delivery processes but also complicated the decision-making process.Facing with various commodity categories and complex replenishment-delivery processes,one of the main challenges of the logistics operations is to rationally describe the customer demands of small batches and uncertainties.It is hard to further achieve the high-efficiency and stability in the operation of replenishment-delivery process.Therefore,It has a strong practical significance that how to realize the synergy of multi-product replenishment and delivery under the random demand.This paper investigates the B2 C e-commerce replenishment-delivery coordination problem based on the stochastic fuzzy customer demands.The main contents are as follows:First of all,the hotspots and difficulties of the B2 C e-commerce replenishment-delivery problems at home and abroad are summarized.The research status of the stochastic fuzzy requirements and the solving methods of the multi-product replenishment-delivery problem.are generalized.It is clarified that the fuzzy expectation value theory can simplify the multi-item replenishment-delivery coordination mode based on stochastic fuzzy demand.A multi-item replenishment-delivery coordination model under certain demand conditions and a multi-item replenishment-delivery coordination model under stochastic fuzzy demand conditions is established respectively.The random fuzzy demand is assumed as a triangular fuzzy variable in the model of multi-item replenishment-delivery coordination under stochastic fuzzy demand conditions.The fuzzy variables based on historical data are consided to exist random likelihood judgment.The fuzzy expectation value theory is used to construct the JRD(Joint Replenishment and Delivery,JRD)collaborative model with the goal of cost minimization.In addition,the PSO(Particle Swarm Optimization,PSO)is designed to complete the model solution.And according to the characteristics of the algorithm and the model setting,the program is written by Matlab software.By comparing with the results of Genetic Algorithm,PSO for solving the JRD collaborative model is validated.And the influence of the number of commodity types on the parameter setting of the PSO is investigated.The number of commodity types and the main parameters of the algorithm has changed for observing the diversification of the average cost When the PSO algorithm runs 100 times.And the optimal parameter combination is provided for PSO to solve the random fuzzy demand.Finally,the numerical results are compared to provide a reference for the multi-variety commodity replenishment optimization decision.At the same time,it reveals that the collaborative decision-making process of B2 C e-commerce multi-product selection decision-making process can enhance the ability of cost control.