An Improved C2oDE based on Stochastic Ranking

How to balance diversity and convergence as well as constraint violation and objective function in Constrained Optimization Problems (COPs) is an important and key issue when designing a new Constrained Optimization Evolutionary Algorithms (COEAs). C 2 oDE set a good example on this point, and obtai...

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Veröffentlicht in:Chinese Control Conference S. 2414 - 2418
Hauptverfasser: Si, Chengyong, Shen, Jianqiang, Wang, Chaofeng, Wang, Lei
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: Technical Committee on Control Theory, Chinese Association of Automation 26.07.2021
Schlagworte:
Benchmark testing
constrained optimization
Constraint handling
Convergence
Deb's feasibility-based rule
Evolutionary computation
Linear programming
Optimization
Stochastic ranking
ε-constrained method
ISSN:1934-1768
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Zusammenfassung:How to balance diversity and convergence as well as constraint violation and objective function in Constrained Optimization Problems (COPs) is an important and key issue when designing a new Constrained Optimization Evolutionary Algorithms (COEAs). C 2 oDE set a good example on this point, and obtains promising results. In C 2 oDE, the two Constraint Handling Techniques (CHTs) are adopted fixed in two phases. To verify whether there are some other more efficient combinations, Stochastic Ranking (SR) is adopted to balance the combination. Experimental results show a good performance, which also give some inspiration for other research.
ISSN:1934-1768
DOI:10.23919/CCC52363.2021.9550734