Modified Sand Cat Swarm Optimization Algorithm for Solving Constrained Engineering Optimization Problems

The sand cat swarm optimization algorithm (SCSO) is a recently proposed metaheuristic algorithm. It stimulates the hunting behavior of cat, which attacks or searches for prey according to sound frequency; each aims catch better prey. Therefore, will search location In SCSO algorithm, gradually approach its prey, makes strong exploitation ability. However, in later stage prone fall into local optimum, making it unable find position. order improve mobility and exploration ability this paper, modified (MSCSO) proposed. MSCSO adds wandering strategy. When attacking searching walk with strategy enhances have stronger global After that, lens opposition-based learning added enhance property so that can converge faster. To evaluate effect we used 23 standard benchmark functions CEC2014 performance experiment, analyzed data statistics, convergence curve, Wilcoxon rank sum test, box graph. Experiments show walking position-based had Finally, was test seven engineering problems, also verified practicability