Comprehensive learning cuckoo search with chaos-lambda method for solving economic dispatch problems
| Autor: | Liang Qi, Jian Zhao, Hua Duan, Zhengzhong Gao, Zhenyu Huang |
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| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
education.field_of_study Computer science Population Economic dispatch 02 engineering and technology Lambda Swarm intelligence CHAOS (operating system) Constraint (information theory) Electric power system Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cuckoo search education |
| Zdroj: | Applied Intelligence. 50:2779-2799 |
| ISSN: | 1573-7497 0924-669X |
| DOI: | 10.1007/s10489-020-01654-y |
| Popis: | Economic dispatch (ED) is an important part in the economic operation of power systems. It is an NP-hard problem with multiple practical constraints. This paper proposes a novel approach that combines a swarm intelligence algorithm with a constraint-handling mechanism to solve the ED problem. First, we design a comprehensive learning cuckoo search algorithm with two strengthen strategies. A comprehensive learning strategy is designed to give the algorithm advanced learning ability in high-dimensional and multi-modal environment and thus enhance the search ability. A duplicate elimination strategy is utilized as an elite strategy to improve the evolving efficiency of the algorithm. Then, we propose a constraint-based population generation method named chaos-lambda method to reduce the searching complexity, and a solution repair method to repair unfeasible solutions that violate the constraints. The proposed approach is tested on 5 systems with different benchmarks and compared with the state-of-the-art algorithms. Our approach achieves the best performance on every test. |
| Databáze: | OpenAIRE |
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