1. 基于新型非支配排序的多目标麻雀优化算法.
- Author
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武文星, 田立勤, 王志刚, 张 艺, 吴骏一, and 桂方邁
- Subjects
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SEARCH algorithms , *SPARROWS , *PROBLEM solving , *ALGORITHMS , *COUNTING , *TABU search algorithm , *DIFFERENTIAL evolution - Abstract
Targeting to the deficiency of sparrow search algorithm solved the multi-objective problems, and the problems can easily enter the partial optimization and inferior convergence in the counting process, this paper came up with a kind of improved multi-objective sparrow search algorithm. First of all, this paper used a new-type non-dominated sorting to find the Pareto front. Next, it integrated the polynomial mutation and cosine algorithm into species evolution strategy to strengthen its searching ability. It used the species selection method of competition mechanism to decrease the differentiation caused by partial optimized particle and overall optimized particle in the searching process. Finally, this paper compared the improved algorithm and various kinds of multi-objective algorithm in standard test function. The simulation results show that, the convergence and searching ability of the improved algorithm are all superior than other algorithm. Therefore, this algorithm can effectively address the multiple target optimization problem. [ABSTRACT FROM AUTHOR]
- Published
- 2022
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