Title :
Constraint handling techniques for a non-parametric real-valued estimation distribution algorithm
Author :
Aguirre, A.H. ; Diharce, E.V. ; Coello, C.C.
Author_Institution :
Centre for Res. in Math. (CIMAT), Guanajuato
Abstract :
This article introduces the Non-Parametric Real-valued Estimation Distribution Algorithm (NOPREDA), and its application to constrained optimization problems. NOPREDA approximates the target probability density function by building the cumulative empirical distribution of the decision variables. Relationships and structure among the data is modeled through a rank correlation matrix (Spearmans statistics). The procedure to induce a target rank correlation matrix into the new population is described. NOPREDA is used to solve constrained optimization problems. Three constraint handling techniques are investigated: truncation selection, feasibility tournament, and Stochastic Ranking. NOPREDA´s performance is competitive in problems with inequality constraints. However, a mechanism for properly handling equality constraints remains as part of our future research work.
Keywords :
constraint handling; matrix algebra; optimisation; stochastic processes; constrained optimization problems; constraint handling techniques; cumulative empirical distribution; decision variables; feasibility tournament; nonparametric real-valued estimation distribution algorithm; probability density function; rank correlation matrix; stochastic ranking; truncation selection; Clustering algorithms; Computer science; Constraint optimization; Covariance matrix; Gaussian distribution; Linear matrix inequalities; Mathematics; Probability density function; Probability distribution; Stochastic processes;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
DOI :
10.1109/CEC.2007.4424533
