Opposition based learning ingrained shuffled frog-leaping algorithm

Shuffled frog-leaping algorithm (SFLA) is a kind of memetic algorithm. Randomicity and determinacy, the two keywords of SFLA ensures flexibility, robustness and exchange of information effectively in SFLA. In the basic structure of SFLA, the frogs are divided into memeplexes based on their fitness values where they forage for food. In this study the opposition based learning concept is embedded into the memeplexes before the frog initiates foraging. The proposal is investigated, analyzed and compared with latest variants of SFLA on benchmark functions (unimodal and multimodal) along with a real life problem. The result analysis shows that the proposed variant performs consistently well for different types of problems considered in this study.