Title :
Differential evolution combined with constraint consensus for constrained optimization
Author :
Hamza, Noha M. ; Elsayed, Saber M. ; Essam, Daryl L. ; Sarker, Ruhul A.
Author_Institution :
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
Abstract :
Solving a Constrained Optimization Problem (COP) is much more challenging than its unconstrained counterpart. In solving COPs, the feasibility of a solution is a prime condition that requires the conversion of one or more infeasible individuals to feasible individuals. In this paper, to encourage the effective movement of infeasible individuals towards a feasible region, we introduce a Constraint Consensus (CC) method within the Differential Evolution (DE) algorithm for solving COPs. The algorithm has been tested by solving 13 well-known benchmark problems. The experimental results show that the solutions are competitive, if not better, as compared to the state of the art algorithms.
Keywords :
benchmark testing; constraint theory; evolutionary computation; optimisation; CC method; COP; DE algorithm; benchmark problems; constrained optimization problem; constraint consensus; differential evolution; unconstrained counterpart; Algorithm design and analysis; Asynchronous transfer mode; Equations; Indexes; Optimization; Projection algorithms; Vectors; Constrained optimization; constraint consensus; differential evolution;
Conference_Titel :
Evolutionary Computation (CEC), 2011 IEEE Congress on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-7834-7
DOI :
10.1109/CEC.2011.5949709
