James Jianqiao Yu
余剑峤
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Lecturer

Department of Computer Science

University of York

CSE/139, YO10 5GH, UK

jqyu(at)ieee.org CV Google Scholar
Adaptive Chemical Reaction Optimization for Global Numerical Optimization

Authors
James J.Q. Yu, Albert Y.S. Lam, and Victor O.K. Li

Publication
Proc. IEEE Congress on Evolutionary Computation, Sendai, Japan, May 2015

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.