关键词: 工程设计, 优化, 鲸鱼优化算法, 反馈机制, 越界处理, 时间复杂度

Abstract: To better solve the engineering design optimization problems and improve the optimization performance and application ability of the whale optimization algorithm,the whale optimization algorithm based on piecewise random inertia weight and optimal feedback mechanism was proposed.For the random walk foraging strategy,a feedback mechanism based on the current global optimal solution was introduced to speed up the algorithm's convergence speed and enhance the stability of the solution.The piecewise random inertia weight was introduced into the shrinkage encirclement strategy and the spiral bubble net predation strategy,which improved the optimization accuracy and enhanced the ability of algorithm to jump out of the local extremum.The Cross-border processing was modified and improved to eliminate the potential loss of evolution results.Theoretical analysis proved that the improved algorithm had the same time complexity as the basic whale optimization algorithm.The experimental results of 6 representative comparison algorithms on 12 complex benchmark test functions and 3 engineering optimization design problems showed that the proposed algorithm had significantly better optimization performance,solution stability,applicability and effectiveness to different problems by comparing with 5 other comparison algorithms.

Key words: engineering design, optimization, whale optimization algorithm, feedback mechanism, cross-border handling, time complexity