Research On Low Carbon Transportation Under Distributed Manufacturing Supply Chain Environment

With the development of manufacturing globalization,the method of optimizing the supply chain system through vertical integration is no longer advantageous,More and more companies look for excellent partners and resources in the global scope which may be outthrough the boundaries of the company and even the country's borders.Consequently,the member enterprises in manufacturing supply chain are distributed in different locations and this trend is increasingly evident which causes high transportation costs and massive carbon emissions.To reduce the carbon emissions on the base of traditionally transportation costs,the problems of material pick up and products distribution in the manufacturing supply chain are focus on.The research in the paper mainly includes:(1)For low-carbon pick up transportation problem,the optimization model with the integrated objective function in which the factors of economic and environmental are both taken into consideration.On this basis,the improved genetic algorithm is proposed to get the optimization solution with the constraints of time window,load,and number of vehicles.(2)In order to eliminate the influence of the cost coefficient calculation method in the objective function,and to find more general models and algorithms,on the basis of the previous chapter,the multi-objective optimization model with the shortest path and minimum carbon emissions was designed.Firstly,we will obtain the shortest-range cargo consolidation scheme,and then split and reorganize the acquired routes to obtain vehicles with less carbon emissions and route arrangements.In the design of the algorithm,a phased heuristic method based on genetic algorithm and heuristic conservation algorithm is used to solve gradually.(3)At present,new energy trucks,especially pure electric vehicles,are developing rapidly.They have the characteristics of zero emissions,small load,and short driving range.On the basis of the previous research,considering a variety of models including pure electric vehicles and conventional diesel vehicles,a multi-objective optimization model with minimum distance and minimum carbon emissions was established.Then,a two-phase heuristic algorithm solution was designed based on the characteristics of the model,finally,a cargo consolidation scheme that simultaneously meets the environmental benefits and economic benefits is hunt for through the effective utilization of pure electric vehicles.(4)Considering the issue of low-carbon distribution and transportation,the impact of the production environment on the final distribution plan is considered.A production transport scheduling model that manufacturers with parallel machine production system supply various products to multiple customers was established.The optimization goal is to minimize the carbon emission during the transportation under the premise of meeting the latest delivery time.In terms of algorithm design,firstly,the transport plan with the minimum carbon emission is obtain by means of the genetic algorithm.Then according to the transport quantities,orders can be consolidated and the production batch and the completion time can be determined,on this basis,the production scheduling plan is finally obtained.