Dual Population Genetic Algorithm is an effective optimization algorithm that provides additional diversity to the main population. It deals with the premature convergence problem as well as the diversity problem associated with Genetic Algorithm. But dual population introduces additional search space that increases time required to find an optimal solution. This large scale search space problem can be easily solved using all available cores of current age multi-core processors. Experiments are conducted on the problem set of CEC 2006 constrained optimization problems. Results of Sequential DPGA and OpenMP DPGA are compared on the basis of accuracy and run time. OpenMP DPGA gives speed up in execution.
Dual Population Genetic Algorithm is an effective optimization algorithm that provides additional diversity to the main population. It addresses the premature convergence problem as well as the diversity problem associated with Genetic Algorithm. Thus it restricts their individuals to be trapped in the local optima. This paper proposes Dual Population Genetic Algorithm for solving Constrained Optimization Problems. A novel method based on maximum constrains satisfaction is applied as constrains handling technique and Dual Population Genetic Algorithm is used as meta-heuristic. This method is verified against 9 problems from Problem Definitions and Evaluation Criteria for the Congress on Evolutionary Computation 2006 Special Session on Constrained Real-Parameter Optimization problem set. The results are compared with existing algorithms such as Ant Bee Colony Algorithm, Differential Evolution Algorithm and Genetic Algorithm that have been used for solving same problem set. Analysis shows that this technique gives results close to optimum value but fails to obtain exact optimum solution. In future Dual Population Genetic Algorithm can produce more efficient solutions using alternative constrains handling technique.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.