ABSTRACT
In chemistry, chemical reactions are written in the form of an equation using symbols representing chemical elements and molecules. The mechanisms of chemical reactions are very similar to the mechanisms of selection and variation used in evolutionary algorithms, which lead to the new concept of search and optimization algorithms. In order to improve the computational efficiency and the convergence rate of different optimization techniques, opposition-based learning (OBL) was proposed by Tizhoosh. Lam and Li developed the meta-heuristic optimization algorithm based on the nature of chemical reactions and coined the term chemical reaction optimization (CRO). The CRO algorithm is a very recent addition to the meta-heuristic algorithm family. An extension of the CRO algorithm is proposed for continuous problems by Lam, which has become known as real-coded CRO. Duan and Gan proposed an elitist CRO (ECRO) algorithm incorporating elitist strategies into the framework of CRO, which include elitist selection, evolution, and crossover.
