An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation

Abstract

Binary tournament (BT) selection is known as an established selection operator that has been employed in various problems. However, in the development of evolutionary algorithms (EA), this selection operator has a drawback in providing an efcient implementation of the union procedure, which cannot guarantee a parsimonious knowledge base with reduced number of rules. Terefore, this paper introduces binary-standard deviation (SD) tournament selection into EA as an enhancement of BT that can lead to focus on more exploration in terms of searching for the best solutions. Te proposed selection operator has been experimented within fsh feed formulation in grouper fsh farming as a case study on fnding the minimum cost and fulflling constraints. Tis approach is better than experimental design in terms of costs and time. Te motivation for doing so is to search for alternative ingredients for the grouper fsh, as the price of trash fsh is too luxurious. It is because grouper fsh are carnivorous and need many trash fsh for better growth. Te novelty of the proposed SD tournament selection is compared with BT selection in terms of searching for an efcient but not myopic algorithm. Hence, based on the comparative study, the fndings of the enhanced selection operator towards the EA have been convinced and accepted in terms of better cost and fulflling constraints requirements.