A Multi Measure Improved Firefly Algorithm
| Autor: | Niu Junying, Xiaodong Yang, Zefan Cai |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Optimization problem business.industry Computer science 020209 energy Swarm behaviour 02 engineering and technology Simulated annealing Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Local search (optimization) Firefly algorithm business Focus (optics) Evolution strategy |
| Zdroj: | 2018 2nd IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC). |
| DOI: | 10.1109/imcec.2018.8469598 |
| Popis: | Firefly algorithm is a kind of bionic swarm optimization algorithm, which is simple and convenient. It has been applied in many fields. However, the algorithm has an obvious disadvantage of weak global search ability. When it is applied to complex optimization problems, some measures must be adopted in order to improve its performance. In this paper, five improvements are introduced. The improvements focus on parameter adjustment, topological structure and evolution strategy. The global search ability and local search ability are better balanced. The convergence speed and convergence accuracy are improved. The simulation results show that the performance of the improved algorithm is superior to the basic algorithm and other improved algorithms, and more effective for complex optimization problem. |
| Databáze: | OpenAIRE |
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