Pires, E. J. SolteiroMendes, LuísLopes, António M.Oliveira, P. B. MouraMachado, J. A. Tenreiro2014-03-122014-03-122013978-94-007-4721-0978-94-007-4722-72213-8986http://hdl.handle.net/10400.22/4178This paper addresses the problem of finding several different solutions with the same optimum performance in single objective real-world engineering problems. In this paper a parallel robot design is proposed. Thereby, 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 ε-dominance to promote diversity over the admissible space. The performance of the proposed algorithm is analyzed with three well-known test functions and a function obtained from practical real-world engineering optimization problems. A spreading analysis is performed showing that the solutions drawn by the algorithm are well dispersed.engbook part10.1007/978-94-007-4722-7_13