Research On Green Vehicle Routing Problem Based On Improved Squid Algorithm

With the rapid development of Internet economy,the transformation of logistics and transportation industry has accelerated,but the greenhouse gases such as carbon dioxide produced in the process of logistics and transportation have also caused some environmental pollution.How to effectively reduce the total cost and carbon emissions in the distribution process by rational planning of the distribution vehicle path has gradually become a hot topic in the study of vehicle distribution path.Based on the classic vehicle path problem,this paper takes into account the vehicle fuel consumption cost and carbon emission cost,and makes an in-depth study of the green vehicle path-related problems.Because the GVRP problem belongs to the NP-Hard problem,the calculation time will grow exponentially with the expansion of the problem scale,and it is difficult to obtain a better solution in the limited time.Therefore,it is urgent to find a new method to solve the complex GVRP problem effectively.Group intelligent optimization algorithm is a new type of algorithm to simulate biological evolution or foraging behavior,which has the characteristics of fast convergence speed and strong search ability.Therefore,the group intelligent optimization algorithm is used more and more in solving the GVRP problem,this paper mainly focuses on solving the GVRP problem of the improved squid algorithm in-depth study,the specific content of the study is as follows:1.In view of the shortcomings of the standard squid algorithm in solving the GVRP problem,which is too random in the process of population evolution and the unmanageable direction of population evolution,a discrete squid algorithm(DCOA)is designed,which first uses roulette mechanism to improve the initial population and accelerate the convergence speed of the algorithm;The 2-opt method and the shift method are introduced in local search to further improve the optimization performance of the algorithm,and finally,the simulation experiment is carried out through the Augerat standard data set,and the results are compared with the experimental results of other algorithms to verify the validity and feasibility of the proposed algorithm.2.In order to further study the GVRP problem which is more in line with the development of low-carbon economy,a carbon constrained green vehicle routing problem model is established,and a certain carbon emission penalty cost is set to limit the overall carbon emission of the distribution center.At the same time,a hybrid discrete squid algorithm is designed to solve the model.The pheromone guidance method is introduced in the algorithm.The carbon emission factor and the path length factor are used to jointly determine the transition probability of a customer point.The global search is carried out by the pheromone guided swap method and the pheromone guided shift method,so that the algorithm is fast in the whole search space according to the positive guidance of pheromone Speed to the correct solution space;use or opt method and 3-opt method to help the algorithm jump out of the local optimum,enhance the optimization ability of the algorithm near the optimal solution,expand the search space of the algorithm;finally,through three kinds of examples in the Augerat standard data set,the experimental results are compared with other algorithms to further verify the stability and feasibility of the hybrid discrete squid algorithm It’s not easy.