Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation

The aquaculture farming industry is one of the most important industries in Malaysia since it generates income to economic growth and produces main source of food for the nation. One of the pillars in aquaculture farming industries is formulation of food for the animal, which is also known as feed m...

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Main Author: Rosshairy, Abd Rahman
Format: Thesis
Language:English
English
Published: 2014
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Online Access:https://etd.uum.edu.my/4416/1/s92166.pdf
https://etd.uum.edu.my/4416/7/s92166_abstract.pdf
https://etd.uum.edu.my/4416/
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spelling my.uum.etd.44162023-01-11T04:58:53Z https://etd.uum.edu.my/4416/ Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation Rosshairy, Abd Rahman QA Mathematics The aquaculture farming industry is one of the most important industries in Malaysia since it generates income to economic growth and produces main source of food for the nation. One of the pillars in aquaculture farming industries is formulation of food for the animal, which is also known as feed mix or diet formulation. However, the feed component in the aquaculture industry incurs the most expensive operational cost, and has drawn many studies regarding diet formulation. The lack of studies involving modelling approaches had motivated to embark on diet formulation, which searches for the best combination of feed ingredients while satisfying nutritional requirements at a minimum cost. Hence, this thesis investigates a potential approach of Evolutionary Algorithm (EA) to propose a diet formulation solution for aquaculture farming, specifically the shrimp. In order to obtain a good combination of ingredients in the feed, a filtering heuristics known as Power Heuristics was introduced in the initialization stage of the EA methodology. This methodology was capableof filtering certain unwanted ingredients which could lead to potential poor solutions. The success of the proposed EA also relies on a new selection and crossover operators that have improved the overall performance of the solutions. Hence, three main EA model variants were constructed with new initialization mechanism, diverse selection and crossover operators, whereby the proposed EAPH-RWS-Avg Model emerged as the most effective in producing a good solution with the minimum penalty value. The newly proposed model is efficient and able to adapt to changes in the parameters, thus assists relevant users in managing the shrimp diet formulation issues, especially using local ingredients. Moreover, this diet formulation strategy provides user preference elements to choose from a range of preferred ingredients and the preferred total ingredient weights. 2014 Thesis NonPeerReviewed text en https://etd.uum.edu.my/4416/1/s92166.pdf text en https://etd.uum.edu.my/4416/7/s92166_abstract.pdf Rosshairy, Abd Rahman (2014) Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation. PhD. thesis, Universiti Utara Malaysia.
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Electronic Theses
url_provider http://etd.uum.edu.my/
language English
English
topic QA Mathematics
spellingShingle QA Mathematics
Rosshairy, Abd Rahman
Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
description The aquaculture farming industry is one of the most important industries in Malaysia since it generates income to economic growth and produces main source of food for the nation. One of the pillars in aquaculture farming industries is formulation of food for the animal, which is also known as feed mix or diet formulation. However, the feed component in the aquaculture industry incurs the most expensive operational cost, and has drawn many studies regarding diet formulation. The lack of studies involving modelling approaches had motivated to embark on diet formulation, which searches for the best combination of feed ingredients while satisfying nutritional requirements at a minimum cost. Hence, this thesis investigates a potential approach of Evolutionary Algorithm (EA) to propose a diet formulation solution for aquaculture farming, specifically the shrimp. In order to obtain a good combination of ingredients in the feed, a filtering heuristics known as Power Heuristics was introduced in the initialization stage of the EA methodology. This methodology was capableof filtering certain unwanted ingredients which could lead to potential poor solutions. The success of the proposed EA also relies on a new selection and crossover operators that have improved the overall performance of the solutions. Hence, three main EA model variants were constructed with new initialization mechanism, diverse selection and crossover operators, whereby the proposed EAPH-RWS-Avg Model emerged as the most effective in producing a good solution with the minimum penalty value. The newly proposed model is efficient and able to adapt to changes in the parameters, thus assists relevant users in managing the shrimp diet formulation issues, especially using local ingredients. Moreover, this diet formulation strategy provides user preference elements to choose from a range of preferred ingredients and the preferred total ingredient weights.
format Thesis
author Rosshairy, Abd Rahman
author_facet Rosshairy, Abd Rahman
author_sort Rosshairy, Abd Rahman
title Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
title_short Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
title_full Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
title_fullStr Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
title_full_unstemmed Evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
title_sort evolutionary algorithms with average crossover and power heuristics for aquaculture diet formulation
publishDate 2014
url https://etd.uum.edu.my/4416/1/s92166.pdf
https://etd.uum.edu.my/4416/7/s92166_abstract.pdf
https://etd.uum.edu.my/4416/
_version_ 1755875163519320064
score 13.18916