Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection

Fish is one of the main meals among people in many countries. Due to that, the problems of insufficient wild-caught fish and the high market demand have driven the effort for fish farming, especially for grouper since its high commercial value. However, fish feed is costly, while the nutrients’ qual...

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Main Author:	Soong, Cai Juan
Format:	Thesis
Language:	eng eng eng
Published:	2023
Subjects:	TS155-194 Production management Operations management
Online Access:	https://etd.uum.edu.my/10890/1/permission%20to%20deposit-embargo%2036%20months-s96061.pdf https://etd.uum.edu.my/10890/2/s96061_01.pdf https://etd.uum.edu.my/10890/3/s96061_02.pdf
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id	my-uum-etd.10890
record_format	uketd_dc
spelling	my-uum-etd.108902024-01-15T00:36:32Z Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection 2023 Soong, Cai Juan Abdul Rahman, Rosshairy Ramli, Razamin Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Art & Sciences TS155-194 Production management. Operations management SH Aquaculture. Fisheries. Angling Fish is one of the main meals among people in many countries. Due to that, the problems of insufficient wild-caught fish and the high market demand have driven the effort for fish farming, especially for grouper since its high commercial value. However, fish feed is costly, while the nutrients’ quality needs to be prioritized. Thus, a formulation for grouper fish feed is essential involving appropriate combination of ingredients to optimize nutritional balance with minimal cost. Therefore, this research focused on feed formulation for grouper fish taking into consideration suitable 14 ingredients and 15 nutrients. A set of hard and soft constraints was involved with certain penalties given in ensuring grouper’s healthy growth. The main contribution of this research is the development of feed formulation using Evolutionary Algorithm (EA) with four variations of EA, which are Semi-Random Initialization – Binary Tournament Selection - EA (SR-BT-EA), Fibonacci Rabbit Initialization – Binary Tournament Selection - EA (FR-BT-EA), Semi-Random Initialization - Binary- Standard Deviation Tournament Selection - EA (SR-SD-EA) and Fibonacci Rabbit Initialization - Binary-Standard Deviation Tournament Selection - EA (FR-SD-EA). These variations include the enhanced SD Tournament Selection, novel FR Initialization and newly introduced Z-score expression in the fitness value function. The results show that the fitness function of the EA is able to minimize the penalty values related to weight of ingredients and nutrients’ quality. Among the four EA variations, the FR-SD-EA is the most significant formulation achieving lowest cost of RM 407.09 for a 100 kg feed with the best-so-far fitness value of 407.090 and zero penalty. Thus, this research offers a new approach of formulating the right amount of ingredients to produce a high-quality feed containing essential nutrients for the growth of grouper fish at a minimal cost. Moreover, industrial practitioners can take advantage of the flexibility of the EA methodology to readjust the bulk weight of 100 kg to user-preferred weights, with minor modifications to the EA. 2023 Thesis https://etd.uum.edu.my/10890/ https://etd.uum.edu.my/10890/1/permission%20to%20deposit-embargo%2036%20months-s96061.pdf text eng 2026-10-20 staffonly https://etd.uum.edu.my/10890/2/s96061_01.pdf text eng 2026-10-20 staffonly https://etd.uum.edu.my/10890/3/s96061_02.pdf text eng staffonly other doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng eng
advisor	Abdul Rahman, Rosshairy Ramli, Razamin
topic	TS155-194 Production management Operations management TS155-194 Production management Operations management
spellingShingle	TS155-194 Production management Operations management TS155-194 Production management Operations management Soong, Cai Juan Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
description	Fish is one of the main meals among people in many countries. Due to that, the problems of insufficient wild-caught fish and the high market demand have driven the effort for fish farming, especially for grouper since its high commercial value. However, fish feed is costly, while the nutrients’ quality needs to be prioritized. Thus, a formulation for grouper fish feed is essential involving appropriate combination of ingredients to optimize nutritional balance with minimal cost. Therefore, this research focused on feed formulation for grouper fish taking into consideration suitable 14 ingredients and 15 nutrients. A set of hard and soft constraints was involved with certain penalties given in ensuring grouper’s healthy growth. The main contribution of this research is the development of feed formulation using Evolutionary Algorithm (EA) with four variations of EA, which are Semi-Random Initialization – Binary Tournament Selection - EA (SR-BT-EA), Fibonacci Rabbit Initialization – Binary Tournament Selection - EA (FR-BT-EA), Semi-Random Initialization - Binary- Standard Deviation Tournament Selection - EA (SR-SD-EA) and Fibonacci Rabbit Initialization - Binary-Standard Deviation Tournament Selection - EA (FR-SD-EA). These variations include the enhanced SD Tournament Selection, novel FR Initialization and newly introduced Z-score expression in the fitness value function. The results show that the fitness function of the EA is able to minimize the penalty values related to weight of ingredients and nutrients’ quality. Among the four EA variations, the FR-SD-EA is the most significant formulation achieving lowest cost of RM 407.09 for a 100 kg feed with the best-so-far fitness value of 407.090 and zero penalty. Thus, this research offers a new approach of formulating the right amount of ingredients to produce a high-quality feed containing essential nutrients for the growth of grouper fish at a minimal cost. Moreover, industrial practitioners can take advantage of the flexibility of the EA methodology to readjust the bulk weight of 100 kg to user-preferred weights, with minor modifications to the EA.
format	Thesis
qualification_name	other
qualification_level	Doctorate
author	Soong, Cai Juan
author_facet	Soong, Cai Juan
author_sort	Soong, Cai Juan
title	Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
title_short	Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
title_full	Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
title_fullStr	Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
title_full_unstemmed	Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
title_sort	grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2023
url	https://etd.uum.edu.my/10890/1/permission%20to%20deposit-embargo%2036%20months-s96061.pdf https://etd.uum.edu.my/10890/2/s96061_01.pdf https://etd.uum.edu.my/10890/3/s96061_02.pdf
_version_	1794023782870941696

Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection

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