A novel path-based reproduction operator for multi-objective optimization
| Autor: | Chen Fan, Weimin Zhong, Feng Qian, Wei Du, Wenjiang Song |
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| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
General Computer Science Computer science General Mathematics 05 social sciences Evolutionary algorithm 050301 education 02 engineering and technology Multi-objective optimization Operator (computer programming) Simple (abstract algebra) Path (graph theory) Convergence (routing) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Focus (optics) 0503 education Selection (genetic algorithm) |
| Zdroj: | Swarm and Evolutionary Computation. 59:100741 |
| ISSN: | 2210-6502 |
| DOI: | 10.1016/j.swevo.2020.100741 |
| Popis: | A large number of multi-objective evolutionary algorithms (MOEAs) have been proposed for the past two decades. However, few papers focus on the study of reproduction operator in MOEAs. In this work, we propose a novel path-based reproduction operator, termed path evolution (PE), to generate potential solutions more effectively for MOEAs. In PE, there is no mating selection, and the calculation of the evolution path is simple. Moreover, a new gene-sharing operation is proposed. The effectiveness of PE is validated by comparing it with three widely used reproduction operators and two state-of-the-art path-based reproduction operators. It is also reported that PE is very flexible to embed into different categories of MOEAs. The empirical results on three widely used test suites demonstrate the superiority, especially faster convergence ability, of PE. |
| Databáze: | OpenAIRE |
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