Modeling And Optimization Algorithm Of Reverse Logistics Location Based On Energy Consumption

With the deepening of the research on resource reuse,product recycling has attracted the attention of enterprises and academic researchers.In the research of product recycling,the research of reverse logistics network,especially the location of reverse logistics facilities,has always been the focus.In this paper,the energy consumption as a starting point,the carbon emissions and benefits in the reverse logistics network as a functional objective for modeling and optimization,and using the improved gravity optimization algorithm to solve the reverse logistics facility location model,get the excellent set of location schemes.Considering the influencing factors of network facilities construction,this paper evaluates the alternatives with multiple indexes,and makes the final choice of facilities location.The main research contents are as follows:(1)The double objective function optimization model of reverse logistics facility location is constructed.The three-level recycling facilities of recycling center,classification center and processing center are combined with the original logistics system of manufacturers,suppliers and consumers to form a closed-loop logistics system.In order to study the facility location problem of three-level reverse logistics,the capacity of recycling center,classification center,processing center and the transportation volume between different recycling facilities are taken as constraints,and the two objective functions of low-carbon and maximum revenue are used to optimize the location scheme of logistics facilities.The carbon emission target is divided into two parts: Transportation carbon emission and treatment carbon emission.According to the different stages of transportation and treatment,the carbon emission in the process of product recovery is quantified;and the income is divided into four parts according to the different stages of recovery,and the total recovery income is calculated respectively.(2)The improved universal gravitation algorithm is used to solve the location model of reverse logistics facilities,and the Pareto set of location scheme is obtained.By combining the optimization characteristics of classical particle swarm optimization algorithm and universal gravitation algorithm,the two algorithms complement each other,and a hybrid particle swarm optimization algorithm with better optimization performance is obtained.Taking the mobile phone recycling in Jilin Province as an example,it is proved that the hybrid algorithm has excellent convergence performance,meets the needs of solving the facility location model,and obtains the optimal solution set satisfying the double objectives.In addition,the accuracy and stability of the algorithm are verified by different recovery rate and facility capacity.(3)After the Pareto set representing the optimal solution is obtained,combined with the detail model and TOPSIS model,the multi index evaluation method is used to evaluate the excellent scheme set.Nine indexes are selected from three levels of economy,society and technology to construct the evaluation system,which is used to evaluate the advantages and disadvantages of the scheme and to cover the factors that affect the location of facilities to the greatest extent,so as to select the optimal location scheme.In a word,this paper models and analyzes the location of reverse logistics facilities,and establishes two goals of energy consumption and revenue.The multi-objective model is solved by the hybrid particle swarm optimization algorithm.Taking the excellent scheme set solved by the algorithm as the alternative scheme,the advantages and disadvantages of the scheme are evaluated and analyzed by the method of multi index evaluation,and the optimal scheme is finally found out.