| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 96.21 KB | Adobe PDF |
Advisor(s)
Abstract(s)
This 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.
Description
Keywords
Pedagogical Context
Citation
Publisher
Springer