关键词: 元启发式算法, 乌鸦搜索算法, 约束优化问题, 动态感知概率, 莱维飞行策略, 变异更新机制

Abstract: To properly solved the difficulties of engineering constraint optimization problems,a novel metaheuristic algorithm named Crow Search Algorithm (CSA) was studied.The principle and essential procedures of CSA were introduced,and the characteristics of CSA were presented through comparison with other classical optimization algorithms.For complex optimization problems,the dynamic awareness probability,Levy flight strategy and mutation update mechanism were introduced and thus Modified Crow Search Algorithm (MCSA) was developed.Experimental testing results proved that MCSA had excellent performance in search accuracy,stability and search efficiency.For solving constrained optimization problems,Feasibility and Dominance (FAD) rules were incorporated into MCSA,a constraint handling mechanism was constructed.The feasibility and superiority of the algorithm were verified through three engineering constrained optimization problems.

Key words: metaheuristic algorithm, crow search algorithm, constrained optimization problem, dynamic awareness probability, Levy flight strategy, mutation update mechanism