Enhanced selection method for genetic algorithm to solve traveling salesman problem
Genetic algorithms (GAs) have been applied by many researchers to get an optimized solution for hard problems such as Traveling Salesman Problem (TSP). The selection method in GA plays a significant role in the runtime to get the optimized solution as well as in the quality of the solution. Stochas...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://repo.uum.edu.my/22800/1/ICOCI%202017%2069-76.pdf http://repo.uum.edu.my/22800/ http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap02e/PID35-69-76e.pdf |
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| Summary: | Genetic algorithms (GAs) have been applied by many researchers to get an optimized solution for hard problems such as Traveling Salesman Problem (TSP). The selection method in GA plays a significant
role in the runtime to get the optimized solution as well as in the quality of the solution. Stochastic Universal Selection (SUS) is one of the selection methods in GA which is considered fast but it leads to lower quality solution.Although using Rank Method Selection (RMS) may lead to high quality solution, it has long runtime.In this work, an enhanced selection method is presented which maintains both fast runtime and high solution quality.First, we present a framework to solve TSP using GA with the original selection
method SUS. Then, the SUS is replaced by the proposed enhanced selection method.The experimental results show that a better quality solution was obtained by using the proposed enhanced selection method compared to the original SUS. |
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