Optimization Of Purchase Decision In Multi-level Supply Chain Network

With the rapid development of market economy and the increasingly fierce market competition,the scientific decision-making capabilities of enterprises in various aspects such as research and development,procurement,production,and marketing are needed to be improved.As an important determinant of cost,purchasing decision plays an important role in the production and operation activities of enterprises.The cooperation between upstream and downstream enterprises in the supply chain,especially the procurement cooperation in the supply chain network,is needed to be strengthened to adapt to the fierce market competition.At present,the one-to-many and many-to-many secondary supply chain models are extensively studied,but the multi-level supply chain models are rarely involved.Therefore,the optimization of procurement decision in multilevel supply chain network has important research value.Firstly,based on multiple materials,multiple periods,price discounts,considering capacity constraints,and allowing shortages,the problem of order allocation in a many-to-many secondary supply chain is studied.A mathematical model is established with the goal of minimizing expected cost of multi-manufacturers composed of purchase,transportation,shortage and inventory costs.Then on the basis of the secondary supply chain,the problem of order allocation in the tertiary supply chain with distributors is further considered,and a mathematical model aiming at minimizing the cost of the supply chain is established.Because the model involve multiple constraints,multiple suppliers need to be selected in a certain period of purchase.In consideration of price discounts,the maximum and minimum procurement constraints must be met.At the same time,it is needed to ensure that each raw material matching purchase.Many conflicts are created in the order allocation process,and the allocation process is more complicated.According to the characteristics of the two models,the corresponding genetic algorithm double coding chromosomes are designed respectively.The 0-1 coding represents the selection of suppliers,and the integer coding represents the specific purchase quantity.The generation of initial population under multiple constraints is elaborated in detail.After crossover and mutation operations,the second level supply chain generates the illegal chromosome that the demand is not equal to the purchase quantity of manufacturers,and the purchase quantity is adjusted according to the comprehensive unit price of suppliers for repair.The tertiary level supply chain generates the illegal chromosome that the demand is not equal to the purchase quantity of distributors,and the proportion chromosome is introduced for repair.The examples are calculated by genetic algorithm and heuristic algorithm respectively,and the results verify the effectiveness of the designed genetic algorithm.Finally,the modeling and optimization methods in this paper are used for the application of engineering examples.Taking Ningbo injection molding machine supply chain as an example,an order allocation strategy of the tertiary supply chain network of injection molding machine is formulated.It is concluded that the optimized total cost of the supply chain is reduced by 4.43%compared with the actual total cost of the supply chain,which improves the overall competitiveness of the supply chain.