Title :
BIEA: A novel evolutionary algorithm for nonlinear constrained programming
Author :
Jia, Liping ; Zou, Guocheng ; Luo, Chi ; Zou, Jin
Author_Institution :
Coll. of Math. & Inf. Sci., Leshan normal Univ., Leshan, China
Abstract :
Nonlinear constrained problem has been deemed as a hard problem. This paper proposes a kind of evolutionary algorithm for constrained programming. The constrained conditions are converted into an objective and then the constrained programming is transformed into a special bi-objective unconstrained problem. The Pareto concept of multiobjective programming is introduced, then crossover operator using uniform designing method and feasible mutation operator are designed to solve this kind of bi-objective unconstrained programming. The detailed procedure of the algorithm based on two objectives is proposed. Five standard benchmarks are applied to verify the validity of the algorithm. The feasibility and efficiency of the proposed algorithm are shown by comparing with other two algorithms.
Keywords :
Pareto optimisation; constraint handling; evolutionary computation; BIEA algorithm; Pareto concept; bi-objective unconstrained problem; crossover operator; evolutionary algorithm; feasible mutation operator; multiobjective programming; nonlinear constrained programming; uniform designing method; Asia; Automatic control; Constraint theory; Design methodology; Evolutionary computation; Functional programming; Genetic programming; Informatics; Robot control; Robotics and automation; Pareto solution; constraint handling; evolutionary algorithm; multi-objective optimization; uniform designing method;
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
DOI :
10.1109/CAR.2010.5456627