Cooperative micro-differential evolution for high-dimensional problems

High–dimensional optimization problems appear very often in demanding applications. Although evolutionary algorithms constitute a valuable tool for solving such problems, their standard variants exhibit deteriorating performance as dimension increases. In such cases, cooperative approaches have proved to be very useful, since they divide the computational burden to a number of cooperating subpopulations. In contrast, Micro–evolutionary approaches constitute light versions of the original evolutionary algorithms that employ very small populations of just a few individuals to address optimization problems. Unfortunately, this property is usually accompanied by limited efficiency and proneness to get stuck in local minima. In the present work, an approach that combines the basic properties of cooperation and Micro-evolutionary algorithms is presented for the Differential Evolution algorithm. The proposed Cooperative Micro–Differential Evolution approach employs small cooperative ...

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Konstantinos E. Parsopoulos
• Keywords: Differential Evolution Algorithm, Evolutionary Algorithms, GECCO 2009, Optimization, Optimization Problems