The Study Of Urban Common Distribution Route Optimization For Multi-objective And Multi-depot

With the advent of economic integration and the era of globalization of knowledge economy and the continuous improvement of the logistics industry,co-delivery has become one of the important trends in the development of distribution in logistics activities.Co-distribution in the"common" word,compared with the traditional distribution model has the following aspects of improvement:reduce logistics costs,improve logistics efficiency,while reducing the traffic vehicles in transit to ease the pressure on urban transport,saving social costs and reduce the Environmental pollution.Co-delivery in the developed countries has long been a trend,and has been widely practical application.The development of China's common distribution is not perfect yet.The problems of the integration of existing distribution resources and the energy consumption in the distribution process are all problems to be solved urgently in the city common distribution.This paper first analyzes the background of the domestic logistics industry for the low utilization of logistics resources and the ecological environment brought by logistics and distribution,combing the research results at home and abroad from the perspective of urban distribution operation mode,multi-objective problem optimization and particle swarm optimization.On this basis,taking into account the sharing of vehicles in the common distribution and the actual delivery of personalized customer needs,distribution vehicles in the completion of each stage of the last customer point delivery service,do not necessarily return to the departure depot,you can choose the nearest Garage parking,or based on the principle of resource sharing to reduce costs,parking vehicles parked in the open partner.Each delivery phase are independent,distribution yard distribution vehicles with the changing distribution needs to adjust the number of yard vehicles.Therefore,an optimization model of open vehicle routing considering multi-objective multi-car park is constructed,which takes carbon emission,distribution cost and number of vehicles as optimization objectives.Then based on the multi-objective particle swarm optimization algorithm design,through the particle update design and dynamic inertia weight update,tabu list tabu search algorithm introduced in the process of finding the individual extremum and global pole Value to improve the search breadth of the algorithm,search speed and search accuracy,to avoid falling into the local optimum.Finally,the Pareto solution set obtained by the algorithm is processed by the pruning strategy of the external set,and the feasible solutions are obtained according to the combination of different optimization objectives.Finally,taking a certain day's delivery tasks of an enterprise as a practical application case analysis to solve the superiority of verification models and algorithms.And summarize and prospect for this thesis.