Optimization problems are divided into numerical optimization problems and combinatorial optimization problems. Genetic algorithms (GAs) are applied to solve optimization problems widely. GAs with multi-parent crossover are often used to solve numerical optimization problems. However, no effective multi-parent crossover is used for combinatorial optimization problems. Partially mapped crossover (PMX) is the most popular crossover for combinatorial optimization problems. In this thesis, we propose multi-parent partially mapped crossover (MPPMX). A large amount of experimental results show that the improvement ratio of MPPMX reaches 38.63 % over PMX. The p-values of t-test on the difference between MPPMX and PMX range from 10-6 to 10-14, which indicates the significant improvement of MPPMX over PMX.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0831106-160453 |
| Date | 31 August 2006 |
| Creators | Su, Chien-hao |
| Contributors | Chung-Nan Lee, Chuan-Kang Ting, Kuo-sheng Cheng, Pao-Ta Yu, Jung-Hsien Chiang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0831106-160453 |
| Rights | withheld, Copyright information available at source archive |
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