Chaotic Sand Cat Swarm Optimization

In this study, a new hybrid metaheuristic algorithm named Chaotic Sand Cat Swarm Optimization (CSCSO) is proposed for constrained and complex optimization problems. This combines the features of recently introduced SCSO with concept chaos. The basic aim to integrate chaos feature non-recurring locations into SCSO’s core search process improve global performance convergence behavior. Thus, randomness in can be replaced by chaotic map due similar better statistical dynamic properties. addition these advantages, low consistency, local optimum trap, inefficiency search, population diversity issues are also provided. CSCSO, several maps implemented more efficient behavior exploration exploitation phases. Experiments conducted on wide variety well-known test functions increase reliability results, as well real-world was applied total 39 multidisciplinary It found 76.3% responses compared best-developed variant other chaotic-based metaheuristics tested. extensive experiment indicates that CSCSO excels providing acceptable results.