Research On Distribution Routing Optimization Of Low-carbon Logistics Based On Genetic Algorithm

Under the background of countries paying attention to low-carbon economy andsustainable development strategy, China has been the great power of energy consumptionand carbon emissions, it faced pressure of environmental pollution and increasinglyserious energy consumption, realizing the sustainable development through thelow-carbon economy development mode has become an inevitable trend. At present, oneof the main sources of carbon emissions is the burning of fossil fuels in transportationindustry and it has drawn significant attention. Therefore, the transportation industry musttake the responsibility of environmental protection, carry out low-carbon transportationpolicy, and speed up the development of green low-carbon environmental transportationmode.This paper mainly studies vehicle routing optimization problem with soft timewindows and multiple distribution centers, simultaneously the low-carbon factors are alsoconsidered. Firstly, this paper starting from the related theory of vehicle routing problemcombines with the characteristics of low-carbon logistics, considering the influence ofvehicle distance to fuel consumption and carbon dioxide emissions, establish the lowcarbon vehicle routing model with soft time windows and the low carbon vehicle routingmodel of multiple distribution centers, the aim is to minimize the total cost. On this basis,we solve the problem through the basic principle of genetic algorithm, according to thedemand of practical research and model, then program with MATLAB and achieve themodel solution. At the end, we collect experimental data from a retail enterprise in thelocal area, select two actual distribution data as experimental data to verify two modelsand genetic algorithm.Model comparison and numerical analysis show that low carbon vehicle routingscheme can achieve an optimal distribution route. The scheme is based on the model inthis paper and adaptive genetic algorithm, and it has the advantages of saving logisticsdistribution cost and improving economic benefit; as a result, this paper achievedminimum logistics costs and meet the needs of real customers. In the paper, numericalresults of example verify the feasibility of two different kinds of low-carbon path planning programs, and provide a new theoretical method for energy-saving, emission reduction.Besides, the results also provide referential solutions for the logistics enterprises toimprove the personalized low-carbon demand of customer.