Research On Multimodal Optimization Method And The Tsp Application Bsaed On WOA

In the real world,many problems in the fields of computer,biology,chemical industry,aerospace and so on belong to multimodal optimization or traveling salesman problems.For example,parameter design of fuzzy systems and risk investment can be converted into multimodal functions to solve extreme values problems,vehicle transportation route planning and disaster evacuation route design are all based on the traveling salesman problem model.Studying how to deal with multimodal optimization problems and traveling salesman problems efficiently and quickly can provide good solutions for related problems in real life,and has important research value and practical significance.The natural heuristic algorithm has become the mainstream method to deal with these two problems because it is simple to operate and only requires corresponding heuristic information to guide the search direction.As an emerging natural heuristic algorithm,the whale optimization algorithm has been proved to have strong performance in handling optimization problems.Therefore,in this paper,the whale optimization algorithm is used as the optimization method to deal with these two problems.Aiming at the two problems mentioned above,this paper proposes a multimodal whale optimization algorithm for processing multimodal optimization problems and a discrete whale optimization algorithm for solving traveling salesman problem.In order to deal with multimodal problems,two clustering algorithms are introduced as niche methods,and the classic whale optimization algorithm is modified to adapt to multimodal optimization problems.A local search strategy based on Gaussian sampling is also introduced to improve the quality of the solution.In order to deal with the traveling salesman problem,this paper redesigns the three algorithm parts of classic whale optimization algorithm,including encircling prey,bubble-net attacking and random search for prey,and uses 2-opt local search algorithm to optimize the partial solutions to improve the accuracy of the solution to bring it closer to the optimal solution.Finally,experiments are used to prove the effectiveness of multimodal whale optimization algorithm on the multimodal optimization problem and discrete whale optimization algorithm on traveling salesman problem,respectively.In addition,the multimodal whale optimization algorithm is compared with two advanced multimodal optimization algorithms to verify the superiority and competitiveness of the multimodal whale optimization algorithm.Comparing discrete whale optimization algorithm with three optimization algorithms for traveling salesman problem,it is proved that the discrete whale optimization algorithm have advantages and is stable in traveling salesman problems.