Title :
Differential evolution with a mix of Constraint Consenus methods for solving a real-world Optimization Problem
Author :
Hamza, Noha M. ; Sarker, Ruhul A. ; Essam, Daryl L.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Abstract :
Over the last few decades, real world constrained optimization has become an important research topic in the evolutionary computation field. The Economic Load Dispatch is one of the well-known complex practical problems. The problem is usually represented by a non-convex constrained optimization model. In this paper, we propose to use an ensemble of three different Constraint Consensus (CC) methods within the Differential Evolution algorithm to solve the Economic Load Dispatch problem. During the evolution process, an adaptive mechanism is used to assign the infeasible solutions to each CC method with the emphasis on the best performing one. The experimental results show that the proposed algorithm is not only able to reach the 100% feasibility ratio, but that it is also able to obtain better solutions in comparison to the state-of-the-art algorithms.
Keywords :
concave programming; evolutionary computation; power generation dispatch; CC methods; adaptive mechanism; constraint consenus methods; differential evolution algorithm; economic load dispatch problem; evolutionary computation field; nonconvex constrained optimization model; real-world constrained optimization problem; Economics; Equations; Generators; Mathematical model; Optimization; Projection algorithms; Vectors; Constrained optimization; constraint consensus; differential evolution; economic load dispatch;
Conference_Titel :
Evolutionary Computation (CEC), 2012 IEEE Congress on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1510-4
Electronic_ISBN :
978-1-4673-1508-1
DOI :
10.1109/CEC.2012.6252904