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The Ethereal
Adaptive Chemical Reaction Optimization for Global Numerical Optimization
July 09, 2015 ยท Declared Dead ยท ๐ IEEE Congress on Evolutionary Computation
"No code URL or promise found in abstract"
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Authors
James J. Q. Yu, Albert Y. S. Lam, Victor O. K. Li
arXiv ID
1507.02492
Category
cs.NE: Neural & Evolutionary
Citations
7
Venue
IEEE Congress on Evolutionary Computation
Last Checked
4 months ago
Abstract
A newly proposed chemical-reaction-inspired metaheurisic, Chemical Reaction Optimization (CRO), has been applied to many optimization problems in both discrete and continuous domains. To alleviate the effort in tuning parameters, this paper reduces the number of optimization parameters in canonical CRO and develops an adaptive scheme to evolve them. Our proposed Adaptive CRO (ACRO) adapts better to different optimization problems. We perform simulations with ACRO on a widely-used benchmark of continuous problems. The simulation results show that ACRO has superior performance over canonical CRO.
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