A standard deviation selection in evolutionary algorithm for grouper fish feed formulation

• Main Authors: Soong, Cai Juan, Ramli, Razamin, Abdul Rahman, Rosshairy
• Format: Conference or Workshop Item
• Language: English
• Published: AIP Publishing LLC 2016
• Subjects: QA Mathematics
• Online Access: http://repo.uum.edu.my/20666/1/AIP%20CP%201782%201%205.pdf; http://repo.uum.edu.my/20666/; http://doi.org/10.1063/1.4966086
• Institution: Universiti Utara Malaysia

Malaysia is one of the major producer countries for fishery production due to its location in the equatorial environment.Grouper fish is one of the potential markets in contributing to the income of the country due to its desirable taste, high demand and high price.However, the demand of grouper fish is still insufficient from the wild catch.Therefore, there is a need to farm grouper fish to cater to the market demand.In order to farm grouper fish, there is a need to have prior knowledge of the proper nutrients needed because there is no exact data available.Therefore, in this study, primary data and secondary data are collected even though there is a limitation of related papers and 30 samples are investigated by using standard deviation selection in Evolutionary algorithm.Thus, this study would unlock frontiers for an extensive research in respect of grouper fish feed formulation.Results shown that the fitness of standard deviation selection in evolutionary algorithm is applicable.The feasible and low fitness, quick solution can be obtained. These fitness can be further predicted to minimize cost in farming grouper fish.