Several approaches are proposed to solve global numerical optimization problems. Most of researchers have experimented the robustness of their algorithms by generating the result based on minimization aspect. In this paper, we focus on maximization problems by using several hybrid chemical reaction optimization algorithms including orthogonal chemical reaction optimization (OCRO), hybrid algorithm based on particle swarm and chemical reaction optimization (HP-CRO), real-coded chemical reaction optimization (RCCRO) and hybrid mutation chemical reaction optimization algorithm (MCRO), which showed success in minimization. The aim of this paper is to demonstrate that the approaches inspired by chemical reaction optimization are not only limited to minimization, but also are suitable for maximization. Moreover, experiment comparison related to other maximization algorithms is presented and discussed.
Keywords: Chemical reaction optimization; Maximization; Mutation operator; Polynomial mutation
Published on: Mar 7, 2017 Pages: 1-11
Full Text PDF
Full Text HTML
DOI: 10.17352/tcsit.000004
CrossMark
Publons
Harvard Library HOLLIS
Search IT
Semantic Scholar
Get Citation
Base Search
Scilit
OAI-PMH
ResearchGate
Academic Microsoft
GrowKudos
Universite de Paris
UW Libraries
SJSU King Library
SJSU King Library
NUS Library
McGill
DET KGL BIBLiOTEK
JCU Discovery
Universidad De Lima
WorldCat
VU on WorldCat
PTZ: We're glad you're here. Please click "create a new query" if you are a new visitor to our website and need further information from us.
If you are already a member of our network and need to keep track of any developments regarding a question you have already submitted, click "take me to my Query."