The IUP Journal of Information Technology
Applications of Genetic Algorithm in Water Resources Management and Optimization

Article Details
Pub. Date : Mar, 2021
Product Name : The IUP Journal of Information Technology
Product Type : Article
Product Code : IJIT30321
Author Name :Garima Tyagi, Rohit Singh and Abid Hussain
Availability : YES
Subject/Domain : Engineering
Download Format : PDF Format
No. of Pages : 13

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Abstract

It is the need of current scenario that water resource is to be retained and maintained. Different types of models have been applied for the optimization of Water Resource Management. Different researchers have applied and used many algorithms to solve optimization problems. Genetic Algorithm (GA) is one of the evolutionary algorithms and research has been done on the use of GA in the Water Resource Management Optimization (WRMO). The paper reviews different applications applied so far, their usefulness and also their scope in the development of future models for water resource planning and optimization.


Description

Water is a natural resource and it is vital for all the living organisms. For human beings, it is essential for living a healthy and disease-free life. Water is essential for every one for their survival on the earth. Only 1% of water is available in fresh form that can be used directly without any type of filtration; rest of the water is available either in sea or in frozen form in mountains and glaciers (Oluwatosin et al., 2013). As the population on the earth is increasing tremendously and due to increasing industrialization, water contamination is becoming very high. Due to all such reasons, water resources are decreasing day-by-day and having high impact on the life of living organisms. It is important to preserve the water resource and use it efficiently. Different evolutionary algorithms have been used for the planning and management of water resources (Oluwatosin et al., 2013). Out of these different algorithms, Genetic Algorithm (GA) is one, and wide research has been done on the use of GA for Water Resources Management Optimization (WRMO).


Keywords

Genetic Algorithm (GA), Soft computing, Water resources, Water Resources Management and Optimization (WRMO)

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ISBN: 978-81-314-2793-4
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