A Two-Stage Crow Search Algorithm for Solving Optimization Problems
International journal of intelligent engineering and systems · 2023
This paper proposes a novel metaheuristic technique called two-stage crow search algorithm (TS-CSA).The TS-CSA extends the original crow search algorithm (CSA), that mimics the intelligent foraging behavior of crows.TS-CSA integrates a two-stage search process to improve the CSA in three aspects.First, the two search stages are designed to balance the algorithm's global search and local search capabilities.Second, TS-CSA incorporates a "leaders group" to enable high-quality individuals to guide other individuals and perform global searches by expanding the search space using the best individuals.Third, TS-CSA proposes a new local search strategy for fine-tuning the individuals of the first stage.The proposed TS-CSA and the original CSA are evaluated alongside other metaheuristic algorithms: Grey wolf optimizer (GWO), marine predators algorithm (MPA), and pelican optimization algorithm (POA) using a well-known benchmark of thirteen optimization functions.These functions are commonly employed to assess optimization algorithms due to their complex landscapes and multiple local optima.The results show that the TS-CSA outperforms all competing algorithms, including the original CSA, in terms of convergence and solution quality across all two categories of optimization functions.Furthermore, the proposed algorithm shows potential for solving complex optimization problems across various domains, making it a valuable tool for practitioners and researchers in related optimization fields.