Multi-period Supply-Chain Distribution Network Optimization Under Constraints Of Fuzzy Time Windows And Mixed Transport

With the market competition intensifies, the supply chain is in a complex and dynamic environment, therefore, to optimize the supply chain distribution system under multi-cycle dynamics, is a trend of optimization of supply chain and distribution network. Mixed Transport (the combination of matching transport and not matching transport) as a new distribution model, can effectively solve the supply chain distribution of empty transport problems, reducing the supply chain distribution costs. However, in the prior studies, the mixed mode of transportation is used in the case of a single-period operation of the supply chain, ignoring the system at different times in the dynamic continuity, which may cause deviation of the best results in practice. Therefore, the study of dynamic multi-period distribution network problems under mixed-transport mode is more practical and has more significance.Further, there are a large number of unpredictable factors in the supply-chain distribution of the real environment. These uncertainties would cause a disturbance and influence of the arrival time of the distribution vehicle, this lead to the presence of the fuzzy customer time-window and fuzzy distribution time of the vehicle in the distribution network. Therefore, combining the fuzzy-time theory and the distribution network optimization theory is more in line with reality, it has certain research value.This paper carries on the study of the multi-cycle distribution network under the mixed transport mode and solves the problem of combining the fuzzy time theory. It is written standing on multiple angles, contains that considering the dynamic characteristic of the distribution system, the uncertainty of distribution time, fuzzy customer time-windows and the various types of vehicles. According to these factors bring up the multi-constrained, multi-period hybrid vehicle transportation and distribution network optimization problem with fuzzy time-window, and apply this thought to a multi-plant, multi-client point, multi-vendor supply chain tertiary distribution network, then built two 0-1 optimization models:the first one is a single-period optimization model with Fuzzy Time constraints of mix-transportation distribution network, the other is a multi-period optimization model with Fuzzy Time constraints of mix-transportation distribution network. Model based on the above ideas, more in line with the actual situation of logistics and distribution activities, therefore, has great research value.In order to get the solution of the model, this paper uses the PSO intelligence optimization algorithm because of its high efficiency and accuracy. Through practical examples to verify the validity of the two models and particle swarm algorithm. Meanwhile, change the value of the parameters in PSO and the vehicle unit transport costs and start the experiment. Through the contrast to the experiments verify that the parameters is important for the PSO algorithm and the model is stable. Stable model can help the companies to make long-term decisions with good guidance.Results of the several examples show that the multi-period supply-chain distribution model is superior than the single-period supply-chain distribution model. It can effectively allocate and plan the resources which enterprise owned, so that make the cost optimization resulting lower.