Research On Low-carbon Logistics Distribution Route Based On Improved Genetic Algorithm

In the report entitled "Vigorously develop circular economy to help achieve carbon peak and carbon neutrality",China proposed to achieve "carbon peak" by 2030 and "carbon neutrality" by 2060.The report of the 20 th National Congress of the Communist Party of China pointed out that we should promote green development and harmonious coexistence between human and nature.In the era of low carbon economy,logistics and transportation occupy an important part of carbon emissions.Therefore,logistics and transportation need to be put on the agenda to reduce carbon dioxide emissions that caused by logistics and distribution.Therefore,in the process of model building,the carbon emission cost is introduced into the vehicle routing optimization model with time windows.This study conforms to the concept of green development,which is conducive to China’s sustainable development path,and actively and steadily promote carbon peak and carbon neutrality.This paper carefully combs the low carbon logistics vehicle routing problem with time windows and its solution methods,introduces carbon emission cost into the enterprise logistics cost,and establishes a vehicle routing optimization model with time windows constraint with the minimum total cost of the enterprise as the objective function.Aiming at the disadvantage that genetic algorithm is easy to fall into local optimum,this paper combines genetic algorithm with neighborhood search algorithm,proposes GA-LNS algorithm,and proposes a fitness function based on parameter dynamic adjustment and an improved destroy operator,and verifies the effectiveness of the algorithm in two ways.First,solve the Solomon standard test instances.Compared with traditional genetic algorithm and other traditional algorithms,GA-LNS algorithm has better solution performance.Secondly,taking the drug distribution of A pharmaceutical company as an example,then use GA-LNS algorithm to solve this problem.Comparing the traditional genetic algorithm with other traditional algorithms,it is found that the total cost of the optimal solution of the GA-LNS algorithm is the lowest,and the variance,coefficient of variation and other statistical indicators of the solution result of the algorithm are significantly lower.It indicates that the GA-LNS algorithm has strong robustness,and further confirms the stable and efficient performance of the GA-LNS algorithm,and it can effectively reduce the carbon emission cost of logistics and distribution.