Research On The Optimization Of Inventory-Routing Problem For Biomass Resource Supply Chain

The biomass resources in China are abundant and widely distributed,the current main problem is how to deal with and utilize the increasing biomass resources.The biomass resource supply chain is a logistics system for the storage,processing and transportation of biomass resources,which includes two important decision-making problems: inventory of collection facilities and vehicle routing.The choice of inventory and vehicle routing will directly and profoundly affect the operating cost and efficiency of the entire logistics system.Therefore,this study proposes to optimize the inventory-routing problem for biomass resource supply chain to minimize the total cost.The output and demand in the biomass resource supply chain are dynamic,there is a gap between the supply of biomass raw materials and actual demand,the gap in the biomass resource supply chain will lead to the bullwhip effect.Considering collection facility inventory and vehicle routing problems separately creates a bullwhip effect leading to higher costs.Also the two decisionmaking problems of inventory and routing have an inverse relationship between benefits.Therefore,this dissertation integrates and optimizes these two problems,which is different from the past,so as to achieve the purpose of most effectively reducing the impact of the reverse relationship between benefits and the bullwhip effect,and to minimize the total cost of the biomass resource supply chain.The integrated inventory-routing problem of the biomass resource supply chain effectively coordinates the decision of the collection facility inventory and vehicle routing,and avoids ignoring the inventory cost when reducing the transportation cost,and optimizes the sum of the two costs.A mixed-integer programming model was developed to determine collection facility inventory and vehicle routing with the goal of minimizing the total supply chain cost.In order to solve the problems that meet the actual situation,it is necessary to develop algorithms with high computational efficiency,and the time cost of accurate algorithms is too high when solving large-scale cases.In this study,a hybrid tabu search algorithm(HTSA)based on neighborhood search and tabu search was developed to realize efficient decision-making of the case.By comparing the exact solution obtained by CPLEX with the calculation results of HTSA,the results show that HTSA can obtain an approximate solution that is very close to the exact solution and saves more time.