Research On Imbalance Of Logistics Supply And Demand In Supply Chain

With increasingly prominent trend of economic globalization, the competition among enterprises is gradually transfered into supply chains'competition. As logistics is an important part of supply chain, it plays an important role in responding rapidly to the demand change of supply chain. The effective logistics management can respond rapidly to the customer demand, join rapidly the material flow of supply chain, and reduce supply chains'logistics cost. However, due to the demand uncertainty and complexity of supply chain system and so on, the imbalance of logistics supply and demand exists in every nodes of supply chain, it results in the falling of logistics efficiency and increasing of logistics cost. So, how to reduce logistics supply and demand imbalance of supply chain has an important significance to increase supply chain competition and respond rapidly customer demand and optimize supply chain management.The paper aims at the problem of logistics supply and demand imbalance of supply chain, analyzes the reasons of logistics supply and demand imbalance in supply chain environment, and sums up the reasons to five aspects: complexity of supply chain system, insufficiency of information share, uncertainty of demand, uncertainty of supplier's service quality, management confusion of production logistics. According to the five reasons, we discuss the control mechanism how to reduce logistics supply and demand imbalance, analyze and research in detail at the five aspects: information share of supply chain, supply chain multi-echelon inventory control, third party logistics service supplier selection, third party logistics'subcontract supplier selection and vehicle loading.The primary innovations are as follows:(1)Based on grid technology, we established the application frame of supply chain information share, analyzed in detail the realization of application frame, and provided a feasible method to realize the supply chain heterogeneous information share of low cost and high capability and easy integration.(2)Aiming at unknown demand probability distributing, we propose the model of robust optimization model of supply chain multi-echelon inventory systems, the robust solution algorithm is given based on certainty scenarios'solution algorithm, the model realize minimizing the maximum percentage deviation between all scenarios and corresponding scenarios'lowest cost. The result analysis for example indicate that robust optimization model can avoid effectively risk of inventory cost increase, and provide a feasible method to control supply chain multi-echelon inventory systems'cost.(3)Considering the redundant indexes question of third party logistics service supplier performance evaluate, an evaluation method of 3PLs based fuzzy-rough sets is proposed, by defining the concepts of fuzzy similarity relation and fuzzy similarity classes of objects, the indexes are reduced, by constructing the approximation degree of the evaluated object to ideal points,the most optimal 3PL is selected.An example proves the validity of this method(4) In order to reduce the subcontract cost and improve third party logistics enterprise's service quality gradually, a bi-level programming model to describe the game relationship between third party logistics enterprise and subcontract supplier is put forward, a concept on measuring subcontract supplier's service quality was presented as"synthetically expressive degree". A genetic algorithm to solve model were designed. By analyzing and comparing of the sample result, when subcontract supplier selection is long-term and it is carried out repetitiously, the method is good at inspiriting subcontract supplier to cut down price and improved service quality at the same time.(5) In order to take both logistics center serving quality and maximal revenue into consideration under vehicle capacity constraint,we proposed a two phases loading model of logistics center, a genetic algorithm to solve the model was set up . The loading experiment is done by using the data of a logistics center, and the experiment result shows that the method is feasible and effective to improve the revenue of logistics center.