'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
This paper presents a genetic algorithm to optimize
uni-objective problems with an infinite number of optimal
solutions. The algorithm uses the maximin concept and
-dominance to promote diversity over the admissible space. The
proposed algorithm is tested with two well-known functions.
The practical results of the algorithm are in good agreement with the optimal solutions of these functions. Moreover, the proposed optimization method is also applied in two practical real-world engineering optimization problems, namely, in radio frequency circuit design and in kinematic optimization of a parallel robot. In all the cases, the algorithm draws a set of optimal solutions. This means that each problem can be solved in several different ways, all with the same maximum performance.N/
