Research On Intelligent Optimization Algorithm And Fitness Landscape Of Vehicle Routing Problem

Vehicle Routing Problem is one of the hot topics in the field of combinatorial optimization and operations research.The main research is on the optimal vehicle usage plan and optimal vehicle route planning under the constraints.Based on the framework of basic vehicle routing problems,it is important to study various vehicle routing problems that meet the needs of production,operation and operation,and to construct a problem-solving algorithm with high quality and high robustness,which is important for improving the level of production management,and reducing the operation of wood.Theoretical significance and practical value.In this paper,based on a simple vehicle routing problem-traveling salesman problem,Kendall distance and Hamming distance are used to analyze the distribution of fitness terrain and solution,and then the fitness terrain of general vehicle routing problem is studied.To analyze the key factors that affect the solution of the vehicle routing problem,and to address the shortcomings of the vehicle routing problem nodes relying on empirical selection,a new model is constructed,through which the best route point selection and the best route selection can be solved simultaneously.Finally,extending from the vehicle routing problem,a generalized improved genetic algorithm based on fitness terrain is proposed.The main research work and results are summarized as follows:Chapters 1 and 2 introduce the research background,research significance,mathematical definition and mathematical model of the vehicle routing problem in detail,introduce the variant problems and research status of the vehicle routing problem in detail,and classify the evolution of the algorithm and the classification of intelligent optimization algorithms After a brief introduction,the principle,process and advantages and disadvantages of the genetic algorithm are briefly introduced.Finally,the basic principles and evaluation indicators of fitness terrain are introduced.Chapter 3,aiming at the shortcomings that the Hamming distance cannot effectively reflect the difference between different arrangements in the study of fitness terrain,proposes the Kendall distance,which can compare the similarity between arrangements,as the basis of fitness terrain analysis.Quotient problem and vehicle routing problem are analyzed by the terrain,and the distribution of key factors and solutions affecting vehicle routing problem are analyzed.Chapter 4 analyzes the practical application of the vehicle routing problem-the construction of underground logistics networks.In view of the shortcomings of network nodes that usually rely on manual selection,a new model is constructed,which can get the best path node and the best path selection at the same time.The path-based dynamic selection strategy reduces the difficulty of the solution,improves the efficiency of the solution,and performs computer simulation analysis on the traditional model.In Chapter 6,for the randomness of parameter selection in the implementation of genetic algorithms,a dynamic parameter adjustment strategy based on fitness terrain analysis is proposed;population diversity strategy is used to ensure population diversity and prevent premature;population competition strategy It is used to improve the local search ability and global search ability of the algorithm,accelerate the convergence speed of the algorithm and improve the accuracy of the solution,and finally test the algorithm by testing the function set and small-scale vehicle road problems.Finally,the full text is summarized,and the future research is prospected.