Improved Whale Optimization Algorithm Based on Fusion Gravity Balance

In order to improve the shortcomings of whale optimization algorithm (WOA) in dealing with problems, and further accuracy stability WOA, we propose an enhanced regenerative based on gravity balance (GWOA). initial stage, nonlinear time-varying factor inertia weight strategy are introduced change foraging trajectory exploration range, which improves search efficiency diversity. random walk stage encircling excellent solutions protected by gravitational ensure high quality solution. prevent from rapidly converging local extreme value failing jump out, a regeneration mechanism is help population escape optimal value, find better solution within interval through reasonable position updating. Compared six algorithms 16 benchmark functions, contribution values each Wilcoxon rank sum test show that GWOA performs well 30-dimensional 100-dimensional functions practical applications. general, has ability. experiment, compared indexes strategies added were improved. Finally, applied robot path planning three classical engineering applicability verified.