PROJECT TITLE :

Real-Coded Chemical Reaction Optimization

ABSTRACT :

Optimization problems can generally be classified as continuous and discrete, based mostly on the nature of the solution house. A recently developed chemical-reaction-impressed metaheuristic, known as chemical reaction optimization (CRO), has been shown to perform well in many optimization problems in the discrete domain. This paper is dedicated to proposing a true-coded version of CRO, specifically, RCCRO, to unravel continuous optimization issues. We tend to compare the performance of RCCRO with a large number of optimization techniques on a giant set of commonplace continuous benchmark functions. We tend to find that RCCRO outperforms all the others on the common. We have a tendency to additionally propose an adaptive theme for RCCRO which will improve the performance effectively. This shows that CRO is appropriate for solving problems in the continuous domain.