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.
index terms—chemical reaction optimization, continuous
optimization, adaptive scheme, metaheuristic, evolutionary algorithm.