A strategy pool adaptive artificial bee colony algorithm for dynamic environment through multi-population approach

Abstract

Swarm Intelligence is based on developing metaheuristics that are modeled on certain life-sustaining principles exhibited by the biotic components of the ecosystem. There has been a surge in interest for nature inspired computing for devising more efficient models that can find solution to real-world problems using minimal resources at disposal. In this paper, an enhanced version of Artificial Bee Colony algorithm have been proposed that takes on the task of finding the optimal solution in a continuously changing (dynamic) solution space by incorporating a pool of varied perturbation strategies that operate on a multi-population group and synergizing the strategy pool with a set of diversity-inclusion techniques that help to maintain population diversity. © 2012 Springer-Verlag.