Palit, Henry Novianus and Sugiarto, Indar and Prayogo, Doddy and Pratomo, Alexander Thomas Kurniawan (2022) Performance Analysis of a Parallel Genetic Algorithm: A Case Study of the Traveling Salesman Problem. In: 1st International Conference on Information System and Information Technology (ICISIT) 2022, 27-07-2022 - 27-07-2022, Yogyakarta - Indonesia.
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Abstract
Genetic Algorithm (GA) is one of the most popular optimization techniques. Inspired by the theory of evolution and natural selection, it is also famous for its simplicity and versatility. Hence, it has been applied in diverse fields and domains. However, since it involves iterative and evolutionary processes, it takes a long time to obtain optimal solutions. To improve its performance, in this research work, we had parallelized GA processes to enable searching through the solution space with concurrent efforts. We had experimented with both CPU and GPU architectures. Speedups of GA solutions on CPU architecture range from 7.2 to 22.2, depending on the number of processing cores in the CPU. By contrast, speed-ups of GA solutions on GPU architecture can reach up to 172.4.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | genetic algorithm, parallel, OpenMP, CUDA, traveling salesman problem |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Industrial Technology > Informatics Engineering Department |
Depositing User: | Admin |
Date Deposited: | 05 Aug 2022 08:00 |
Last Modified: | 01 Sep 2022 18:33 |
URI: | https://repository.petra.ac.id/id/eprint/19895 |
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