Hierarchical Approaches to Solve Optimization Problems

Optimization is the operation of finding most appropriate solution for a particular problem or set problems. In literature, there are many population-based optimization algorithms solving Each these has different characteristics. Although give optimum results on some problems, they become insufficient to as gets harder and more complex. Many studies have been carried out improve overcome difficulties in recent years. this study, six well-known (artificial algae algorithm - AAA, artificial bee colony ABC, differential evolution DE, genetic GA, gravitational search GSA, particle swarm PSO) were used. its own advantages disadvantages. These tested CEC’17 test functions their performances examined so characteristics determined. Based results, hierarchical approaches proposed order combine achieve better results. The approach refers successful algorithms. eight proposed, performance evaluations structures made functions. When experimental examined, it concluded that can be applied, surpass base states