Improvement And Application Of Whale Optimization Algorithm

In recent years,many swarm intelligence optimization algorithms have been proposed to solve complex optimization problems.Whale optimization algorithm is widely used to solve engineering problems and practical research applications because of its advantages of easy understanding,simple programming and few parameters.Aiming at the problems of poor stability,low accuracy and slow convergence speed of the basic whale optimization algorithm(WOA),this paper proposes a whale optimization algorithm based on elite reverse learning and feedback mechanism(efwoa)The proposed algorithm first optimizes the population by using the elite reverse learning strategy to improve the diversity of the population,and then compares and selects the elite individual with the reverse solution to improve the quality of the population;At the same time,the feedback mechanism is added to prevent the algorithm from falling into local optimization and accelerate the convergence speed of the algorithm through mutual feedback between whales and individual self feedback.The improved algorithm is compared with a variety of cutting-edge optimization algorithms on the benchmark function.The test results show that the algorithm has greatly improved the stability,solution accuracy and convergence speed in the process of solving the test function,and obtained better performance.With the positive changes of various shopping platforms and Internet e-commerce,the role of logistics industry,as a composite industry,in promoting the development of e-commerce and other related industries is self-evident.Logistics distribution is the most critical part of the logistics industry.An effective logistics distribution path can not only save costs,improve enterprise efficiency and establish a good reputation for enterprises,but also reduce a lot of unnecessary expenses for enterprises.Efficient logistics distribution path has also become the goal of logistics enterprises.Taking logistics distribution as the background and optimization as the goal,this paper uses the improved whale optimization algorithm to study the logistics distribution path.Vehicle routing problem(VRP)can be optimized by using some existing heuristic intelligent algorithms.By searching a large number of relevant literature at home and abroad,this paper studies and summarizes the theoretical knowledge of vehicle routing problem,and establishes the mathematical model of vehicle routing problem.The basic whale optimization algorithm and the improved whale optimization algorithm are used to solve the path planning problem respectively.It is proved that the improved whale optimization algorithm can make the logistics path more efficient and the logistics distribution cost lower.It can provide new efficient and feasible solutions for the logistics industry.