Generating Initial Population of Farmland Fertility Algorithm with Chaotic Maps

Abstract

In this study, Farmland Fertility Algorithm, which is one of the meta-heuristic optimization algorithms, has been investigated in detail. Three different approaches and different chaotic maps were used to generate the initial population of the algorithm. The chaotic mapped algorithms were tested with quality test functions and the performance of the algorithm was presented and interpreted through comparative tables and graphs. As a result of the tests, it was observed that the results of the approach of Generating the Whole Population and all dimensions with chaotic maps and the third approach in which the population was produced with one dimensional chaotic maps were generally similar or better with the Farmland Fertility Algorithm. In the second approach, it has been observed that the Farmland Fertility Algorithm, in which the tent (Tent) chaotic map is applied, produces more successful results for almost all dimensions and iterations. In the third approach, successful results were obtained in most of the chaotic map algorithms.