| Whale Optimization Algorithm(WOA)is a population intelligent Optimization Algorithm proposed based on whale predation.Compared with other heuristic algorithms,WOA has obvious advantages,such as fewer parameters,easy implementation and superior performance.It is widely used in data mining,feature selection,facial recognition and other fields.In view of the existing problems of the algorithm,such as low solution accuracy,slow convergence speed and easy to fall into local extremum,a multi-strategy congenerous improved whale optimization algorithm(MSWOA)is proposed.Firstly,the population information guidance mechanism is used to improve the mining efficiency of the global optimal position,so as to avoid the algorithm falling into the local optimal position in the late iteration.Secondly,the improved golden sine algorithm is combined with the process of whale encircling prey to enlarge the search range of the population in the solution space.Finally,inertial weights and nonlinear parameter adjustment strategies are used to balance the global exploration and local development capabilities of the algorithm.By comparison with other intelligent algorithms,comparison with the improved WOA algorithm and optimization performance analysis in high-dimensional cases,it is proved that MSWOA algorithm has better optimization accuracy,convergence speed and solution stability,and the Wilcoxon rank sum test is used to evaluate the MSWOA algorithm has significant differences.According to the convergence analysis,the MSWOA algorithm is proved to be globally convergent,and the MSWOA algorithm also has a good optimization effect for CEC2017 function.For further validation MSWOA solution actual problem ability,the MSWOA algorithm was applied to solve the vehicle path planning problem with time Windows,and simulation experiments were carried out with Solomon data set.The results obtained were compared and analyzed with those of GA and HSWOA algorithm to verify the feasibility and superiority of MSWOA algorithm for solving vehicle path planning problem with time Windows.There are 17 figures,16 tables and 53 references in this paper. |
