A Study On Carbon Emissions Of Vehicle Routing Problem With Time Windows Based On Artificial Bee Colony Algorithm

Vehicle routing problem with time windows (VRPTW) as a major branch of vehicle routing problem (VRP), has been a hot research problem in the field of operations research, and also is a hot and difficult problem in the field of logistics that related to the national economy and people's livelihood of. It requires that the vehicles delivering the right commodities to the right place within the prescribed time, is the study of minimum transportation costs of goods distribution problem.Now at the background of advocate low carbon economy, Green Logistics has recently received increasing and close attention from governments and business organizations. The importance of Green Logistics is motivated by the fact that current production and distribution logistics strategies are not sustainable in the long term. Thus environmental, ecological and social effects are taken into consideration when designing logistics policies, in addition to the conventional economic costs. The environmentally sensitive logistic policy itself requires changing the transportation scheme and shifting it onto a sustainable distribution network with fewer negative impacts on the environment and the ecology, owing to the undeniable fact that transportation accounts for the major part of logistics. So the study of the carbon emissions of VRPTW problem has very important practical significance.This article give a simple review of the definition and models of vehicle routing problem at first, and introduce a taxonomic framework of its extension. Then focuses on the characteristics and the model of VRPTW, and sums up the current conventional methods to solve VRPTW. To solve the models mentioned in this paper. After that we introduced the Artificial Bee Colony Algorithm (ABC)-a swarm intelligent algorithm, Algorithm design can be divided into two parts:The first part, according to the time windows and vehicle capacity constraints of VRPTW, and combined with the successful method that current applications to generate initial solution and local search method, to designing a ABC algorithm that is suitable for the problem (ABC1), and feasibility is verified by an standard test set. At last the ABC1 is improved from three sides: onlooker bee, scout bee and local search. Compared with the same test set, proved the superiority of the improved algorithm (ABC2). The second part considering carbon emissions of the vehicle routing problem with time windows and corresponding model is established. Under the same parameters, we using ABC2 to solve the two models, the results are then compared. The result of the experiment were divided into two aspects:firstly, the result of Solomon standard test set improving the effectiveness of ABC2. Secondly, By comparison with the results of the calculation of the two models, shows that although total distance increased slightly in the case of considering carbon, but the reduction of carbon emissions have more apparent, proved that by changing the optimization target to reduce carbon emissions have certain theory operability.