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Fish School Search Algorithm
Published in A Vasuki, Nature-Inspired Optimization Algorithms, 2020
The complex behavioral patterns of fish within groups depend on the species, age, geographic location, environment, habitat, light levels, and other factors. The fish schools are highly coordinated and tightly knit. Some of the schools extend several kilometers in length and several meters in width and depth. The shoal structure alters based on the current activity of the fish such as migration, foraging, and feeding. The size of the shoal also varies to a great extent, from hundreds of fish to millions of fish. They have an advantage of exploring more food patches compared to individual fish. Fish also migrate hundreds to thousands of kilometers, maintaining high speed. Isolated fish have higher stress leading to lower mobility, less adaptation to environment, and lesser exploratory capabilities. Living in groups curtails their movement and freedom to some extent and also food has to be shared, but the advantages of security against attacks and collective foraging outweigh the disadvantages. These characteristics and behavior of fish swarm have been incorporated into the fish school search optimization algorithm.
A Multi-Objective Time – Series Optimization for Optimum Planning Design of Integrative Power System with the Effects of Multi-Dimensional Sources of Uncertainty
Published in Electric Power Components and Systems, 2023
Velmurugan Vaithiyanathan, Venkatesan Mani, Suresh Govindasamy, Jaisiva Selvaraj
Fish School Search (FSS) is a swarm-based optimization that excels in multimodal search issues, but it requires appropriate step definition in particular operators and twice-per-fish fitness function evaluation. This study introduces a simpler, improved FSS with three benefits over the original: high exploitation, one fish fitness measurement at each iteration, and straightforward implementation.