Performance Scaling of Multi-objective Evolutionary Algorithms

@misc{citeulike:319619, abstract = {MOEAs axe getting immense populaxity in the recent past, mainly because of their ability to find a wide spread of Paxeto-optimal solutions in a single simulation run. Vaxious evolutionary approaches to multi-objective optimization have been proposed since 1985. Some of fairly recent ones axe NSGA-II [9], SPEA2 [19], PESA [1] (which axe included in this study) and others. They all have been mainly applied to two to three objectives. In order to establish their superiority over classical...}, author = {Khare, V. and Yao, X. and Deb, K. }, citeulike-article-id = {319619}, keywords = {self}, posted-at = {2005-09-14 14:42:08}, priority = {2}, title = {Performance Scaling of Multi-objective Evolutionary Algorithms}, url = {http://citeseer.ist.psu.edu/597663.html} }

TY - GEN ID - citeulike:319619 L3 - citeulike-article-id:319619 TI - Performance Scaling of Multi-objective Evolutionary Algorithms N2 - MOEAs axe getting immense populaxity in the recent past, mainly because of their ability to find a wide spread of Paxeto-optimal solutions in a single simulation run. Vaxious evolutionary approaches to multi-objective optimization have been proposed since 1985. Some of fairly recent ones axe NSGA-II [9], SPEA2 [19], PESA [1] (which axe included in this study) and others. They all have been mainly applied to two to three objectives. In order to establish their superiority over classical... KW - self AU - Khare, V AU - Yao, X AU - Deb, K UR - http://citeseer.ist.psu.edu/597663.html ER -