Study On Location And Collection Path Optimization Of Straw Collection And Storage Center

The logistics industry plays important role in the producer service industry of China.It is a basic industry with a high degree of openness,wide coverage and tremendous potential market.As the key of logistics transportation,distribution mainly focuses on the optimization of distribution center location and vehicle routes.Straw collection,storage and transportation system optimization also belongs to the category of logistics system optimization.Straw collection and storage center site selection and vehicle routing optimization are two important parts of this problem,which are directly related to the economic benefits of biomass straw recycling enterprises.Therefore,the optimization of Straw collection and storage center site selection and vehicle route has important theoretical significance and application value.Its theoretical significance lies primarily in the innovation of optimization solution method of such NP-Hard problem,and its practical application significance lies in improving the quality of logistics service,enhancing customer satisfaction and reducing logistics cost.Based on systematic studies of logistics facilities location-allocation,mathematical models and optimization algorithms for vehicle routes in the past few years,this thesis proposes a new mathematical model and more effective solution method.to solve the location-allocation problem of straw warehousing center and the vehicle route problem in straw collection.The main research contents of this thesis include:(1)A Nelder-Mead simulated annealing hybrid algorithm(NMSA),was proposed to solve the optimal site-allocation problem of p-median type straw storage center.The proposed NMSA algorithm first initializes the supply side and demand side distribution schemes of straw at the bottom based on the unit transportation cost ordering,then uses the improved Nelder-Mead algorithm(INM)to guide the location of the storage center,and drives the fast-cooling single-layer simulated annealing neighborhood search algorithm(MSANS)to solve the bottom distribution sub-problem.The comparison test results show that the proposed NMSA algorithm is more accurate and efficient than the double-layer simulated annealing algorithm,fruit fly algorithm and improved artificial fish swarm algorithm.(2)A cost-inventory preferred linear programming algorithm(CICLP)was proposed to solve the optimization of site-allocation problem of collection covered straw storage center by using the idea of reducing the location range and linear programming allocation.The proposed CICLP algorithm firstly uses the cost sorting inventory optimization algorithm(CSIC)to narrow the site selection range and generate the optimal site selection scheme,and then uses the linear programming algorithm LP to optimize the straw supply side and demand side distribution sub-problem.The test results showed that the proposed CICLP algorithm has less computation time and cost,and the solution quality is slightly better than that of LINGO.(3)A neighborhood search algorithm(SNS)is proposed to solve the path problem of farmland straw collection vehicles with multiple models,dual targets and limited capacity.The proposed SNS algorithm adopts the multi-layer community information sharing strategy to ensure the balance between global detection ability and local development ability,and periodically equality-update-mixing-sort the neighborhood solutions of straw collection paths generated by swap,reverse and insertion operations,and circulates into subpopulation to obtain the optimal collection path.The comparative test results showed that the comprehensive performance of the proposed SNS algorithm is better than shuffled simulated annealing neighborhood Search(SSANS)algorithm and shuffled neighborhood search(SANS)algorithm,and it is more efficient and accurate.