Abstract

In addressing crucial issues of sustainability, the study focuses on deploying genetic algorithms (GAs) to optimize fishing routes and minimize bycatch in marine fisheries. Overfishing and bycatch, as marine threats, are compounded by the non-selective nature of most fishing practices. This paper analyzes the construction of dynamic multi-dimensional fishing tactics that GAs, inspired by evolution's natural selection, can implement, considering fish location, weather conditions, and other environmental factors. The model aims to balance the requirement of bycatch reduction with optimal resource extraction, minimizing ecological impact. The operational and cost efficiencies of GAs relative to operational fishing methods are also explored in the study. The research, through computational simulations, argues for the potential of GAs in refining procedural choices to tap into sustainable fisheries management. The findings broadly suggest that genetic algorithms might enhance environmental sustainability while maintaining financial profitability in maritime fisheries through reduced bycatch and optimized productivity.