Vehicle Routing Problem With Simultaneous Delivery And Picku

In the logistics and distribution activities, vehicle routing problem is the core issue of the rationalization of distribution, which also has a great influence for the enterprises to improve service levels, reduce logistics costs and increase economic efficiency. In order to minimize distribution costs and maximize returns, for the growing number of return logistics and recycling logistics, picking-up at the same time of delivering will be the main direction of development of modern reverse distribution logistics, so it has a certain theoretical value and practical significance to research vehicle routing problem with simultaneous pick-up and delivery(VRPSPD).This paper mainly study the VRPSPD problem, after analyzing a variety of conventional constraints, we propose the object of this study:VRPSPD with fuzzy and alternative time windows. This paper mainly analyzes and studies from the following aspects.1, which mainly describes the concept of VRP, summarizes the classification of vehicle routing problem according to different criteria, and recalled the Vehicle Routing Problem solving models and algorithms;2, in considering the multi-vehicle, vehicle load limits and the maximum travel distance limitations constraints, through the introduction of fuzzy appointment time and the concept of alternative time windows, we study the Multi-objective vehicle routing problem with simultaneous pick-up and delivery from the perspective of fuzzy customer satisfaction under the condition of uncertain information, and analyzes the algorithm of this model;3, after introducing the composition and characteristics of the standard genetic algorithm, first of all, through analyzing the coding method and the genetic operators, we choose a coding method which based on natural numbers, and three appropriate genetic operators which are easy to deal with.Second, in order to build a suitable fitness function, after dimensionless the three objectives, we transform multiple objectives into a single one by way of weighted summation, and then transform the objective function directly as a fitness function; Finally design a hybrid genetic algorithm to solving multi-objective programming, and use this algorithm for random-weighted and fixed-weighted cases respectively, and after a certain generations of iterations convergence of the optimal solution has been goten,which demonstrates the feasibility and effectiveness of the algorithm. And study the impact of customer satisfaction on the outcome of routing planning; example simulation results show that changes in satisfaction has no significant effect on the results.