Many metaheuristics mimic biological interaction metaphors, such as ant colony, particle swarm, bee foraging, eagle predator behavior, and cuckoo brood parasitism, to solve complex optimization problems. Another type of biological interaction is commensalism, where one species obtains food from the other without harming or benefiting the latter. One of the great objective-driven commensalism phenomena that amaze scientists and have not yet been modeled is the sardine feast. This lecture will elaborate on the foundation of the optimization algorithm, the sardine feast metaheuristic algorithm (SFMO), based on the ecological relationship between all predators involved in the feast. The usefulness of the SFMO is tested to solve several standard benchmark functions. Its results are compared with those obtained by using other metaheuristic algorithms.

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