| Presentation | 2020-05-15 Spy Algorithm for Solving Continuous Optimization Problem Dhidhi Pambudi, Masaki Kawamura, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We proposed the Spy algorithm for solving continuous optimization problems on multimodal functions. The algorithm is one of population-based metaheuristics and is inspired by spy-ring (a cooperated group of spies). The multimodal function may have many local optimums and some of them can be close to the global optimum. Some optimization methods can be trapped in these local optimum and fail to reach the global optimum. Moreover, multimodal function can have many flat plateaus and valleys that make it much harder to solve. The Spy algorithm accommodates exploitation and exploration search in a simple concept and simple operation that make it easy for tuning to get a good result. In order to check the performance of the proposed method, we applied it to some benchmarking tests, which are Ackley, Schwefel, Rastrigin, Dixon-Price, and Michalewicz function on dimension size 3, 5, 10, 15, and 20. We compare the Spy algorithm against Cuckoo Search with and without Levy flight and FFA. Based on the result, the average of error on Ackley, Dixon-Price, and Michalewicz function regardless of dimension size for Spy Algorithm, CS non-Levy, CS Levy, and FFA are 0.48, 18.12, 24.79, and 67921.71. All algorithm was weak on Rastrigin function and very weak on Schwefel function, but the Spy Algorithm still overcame all other compared algorithm. The average computation time regardless of the test functions on all dimension size for Spy Algorithm, CS non-Levy, CS Levy, and FFA are 0.46s, 0.23s, 1.02s, and 5.09s. The Spy algorithm was fast enough and had the best accuracy. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | optimization / continuous / metaheuristic |
| Paper # | NLP2020-5 |
| Date of Issue | 2020-05-08 (NLP) |
| Conference Information | |
| Committee | NLP |
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| Conference Date | 2020/5/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Yamaguchi University (Tokiwa campus) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Hiroaki Kurokawa(Tokyo Univ. of Tech.) |
| Vice Chair | Kiyohisa Natsume(Kyushu Inst. of Tech.) |
| Secretary | Kiyohisa Natsume(Nippon Inst. of Tech.) |
| Assistant | Yutaka Shimada(Saitama Univ.) / Toshikaza Samura(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Nonlinear Problems |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Spy Algorithm for Solving Continuous Optimization Problem |
| Sub Title (in English) | |
| Keyword(1) | optimization |
| Keyword(2) | continuous |
| Keyword(3) | metaheuristic |
| 1st Author's Name | Dhidhi Pambudi |
| 1st Author's Affiliation | Yamaguchi University(Yamaguchi Univ.) |
| 2nd Author's Name | Masaki Kawamura |
| 2nd Author's Affiliation | Yamaguchi University(Yamaguchi Univ.) |
| Date | 2020-05-15 |
| Paper # | NLP2020-5 |
| Volume (vol) | vol.120 |
| Number (no) | NLP-26 |
| Page | pp.pp.23-28(NLP), |
| #Pages | 6 |
| Date of Issue | 2020-05-08 (NLP) |