Title :
Copula Estimation of Distribution Algorithm with PMLE
Author :
Xiaodong Guo ; Lifang Wang ; Jianchao Zeng ; Xueliang Zhang
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
Estimation of Distribution Algorithms (EDAs) have the task to estimate the distribution model of samples. Copula Estimation of Distribution Algorithms (cEDAs) introduce the copula theory into EDAs which divide the multivariate distribution estimation into two parts: the marginal distribution estimation and the estimation of the dependant structure of variables. The parameter of copula influences the shape of dependant structure. PMLE is used in cEDA to estimate the parameter of copula. The experimental results show that the proposed algorithms are feasible and effective.
Keywords :
genetic algorithms; maximum likelihood estimation; parameter estimation; PMLE; cEDA; copula estimation of distribution algorithm; copula parameter estimation; copula theory; genetic algorithms; marginal distribution estimation; maximum likelihood estimation; multivariate distribution estimation; variable dependant structure estimation; Algorithm design and analysis; Evolutionary computation; Joints; MIMICs; Maximum likelihood estimation; Optimization; Estimation of Distribution Algorithms (EDAs); Maximum Likelihood Estimation (MLE); copula;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022139
