Fish-Inspired Heuristics: A Survey of the State-of-the-Art Methods

Abstract The collective behaviour of fish schools, shoals and other swarms in nature has long inspired researchers to develop solutions for optimization problems. Instinct influences the group into schools increase safety, enhance foraging success, promote breeding. According these instinctive behaviours, several fish-inspired algorithms have been introduced solve hard This paper presents a comprehensive survey heuristics, exploring their evolution within context general To our knowledge, this is first cover both main heuristics literature, namely, artificial swarm algorithm (AFSA) Fish school search (FSS), addition by specific species. review covers more than 50 papers published Web Science IEEE databases since 2000. We basic highlighting advantages drawbacks, then detail attempts literature improve complex, multi-objective high-dimensional problems domains. Our work intended provide guidance practitioners purpose further advancing research area heuristics. aspire encourage utilization various fields global real-life applications. findings indicate that are very alive recent still great potential. Several challenges future directions also identified among survey, which can help vibrant line research.