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| Authors: | Johannes Bader, Dimo Brockhoff, Samuel Welten, Eckart Zitzler |
| Group: | Computer Engineering |
| Type: | Inproceedings |
| Title: | On Using Populations of Sets in Multiobjective Optimization |
| Year: | 2009 |
| Month: | April |
| Pub-Key: | bbwz2009a |
| Book Titel: | Lecture Notes in Computer Science. Conference on Evolutionary Multi-Criterion Optimization (EMO 2009) |
| Volume: | 5467 |
| Pages: | 140-154 |
| Keywords: | EMO |
| Publisher: | Springer |
| Abstract: | Most existing evolutionary approaches to multiobjective optimization aim at finding an appropriate set of compromise solutions, ideally a subset of the Pareto-optimal set. That means they are solving a set problem where the search space consists of all possible solution sets. Taking this perspective, multiobjective evolutionary algorithms can be regarded as hill-climbers on solution sets: the population is one element of the set search space and selection as well as variation implement a specific type of set mutation operator. Therefore, one may ask whether a `real' evolutionary algorithm on solution sets can have advantages over the classical single-population approach. This paper investigates this issue; it presents a multi-population multiobjective optimization framework and demonstrates its usefulness on several test problems and a sensor network application. |
| Resources: | [BibTeX] [Paper as PDF] |
