Name
Abstract | ||
|---|---|---|
Nature-inspired meta-heuristic algorithms have dominated the scientific literature in the areas of machine learning and cognitive computing paradigm in the last three decades. Chemical reaction optimisation (CRO) is a population-based meta-heuristic algorithm based on the principles of chemical reaction. A chemical reaction is seen as a process of transforming the reactants (or molecules) through a sequence of reactions into products. This process of transformation is implemented in the CRO algorithm to solve optimisation problems. This article starts with an overview of the chemical reactions and how it is applied to the optimisation problem. A review of CRO and its variants is presented in the paper. Guidelines from the literature on the effective choice of CRO parameters for solution of optimisation problems are summarised. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s12559-017-9485-1 | Cognitive Computation |
Keywords | Field | DocType |
Nature-inspired computing,Biologically inspired algorithm,Physics inspired algorithms,Chemical reaction optimisation | Population,Scientific literature,Computer science,Algorithm,Artificial intelligence,Chemical reaction,Cognitive computing | Journal |
Volume | Issue | ISSN |
9 | 4 | 1866-9956 |
Citations | PageRank | References |
12 | 0.52 | 37 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nazmul H. Siddique | 1 | 125 | 15.71 |
| Hojjat Adeli | 2 | 2150 | 148.37 |