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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cuiru Wang Jiangwei Zhang Jing Yang Chaoju Hu Jun Liu |
| Copyright Year | 2005 |
| Description | Author affiliation: Sch. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding (Cuiru Wang; Jiangwei Zhang; Jing Yang; Chaoju Hu; Jun Liu) |
| Abstract | A modified particle swarm optimization (MPSO) algorithm was proposed. In the modified algorithm, the cooperative mechanism among individuals has been introduced, namely, particles not only adjust its own flying speed according to itself and the best individual of the swarm but also learn from other individuals according to certain probability. Additionally, the mutation of velocity has been added according to the phenomena of the bird flying off at a tangent in the nature. Finally, the tentative behavior is developed, according to the studying law of mankind. This kind of enhanced study behavior accords with the biological natural law even more, and helps to find the global optimum solution more easily. At the same time, concepts of adjustment operator and adjustment sequence were proposed, based on which the MPSO algorithm was successfully rebuilt to solve a typical combinatorial optimization problem: traveling salesman problem, which is a well-known NP-hard problem in the discrete domain. For solving traveling salesman problem, numerical simulation results for the benchmark TSP problems shows the effectiveness and efficiency of the proposed method |
| Starting Page | 689 |
| Ending Page | 694 |
| File Size | 1140398 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780394224 |
| DOI | 10.1109/ICNNB.2005.1614723 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2005-10-13 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Chaos Computer science Ant colony optimization NP-hard problem Genetic mutations Traveling salesman problems Birds Numerical simulation Application software Particle swarm optimization |
| Content Type | Text |
| Resource Type | Article |
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