Marginal Distributions in Evolutionary Algorithms
نویسندگان
چکیده
In this paper, the description of two gene pool recombination operators is described. Both operators are based on the estimation of the distribution of the parents and its use to generate new individuals. The Univariate Marginal Distribution Algorithm (UMDA) uses simple univariate distributions. It is a perfect algorithm for linear problems. The Bivariate Marginal Distribution Algorithm (BMDA) is an extension of UMDA. In BMDA, the most important pair dependencies are taken into account. The dependencies are measured by the Pearson's chi-square statistics. The structure of a problem is being discovered during an optimization. BMDA works well for linear problems as well as for problems with interacting genes.
منابع مشابه
Estimation of LPC coefficients using Evolutionary Algorithms
The vast use of Linear Prediction Coefficients (LPC) in speech processing systems has intensified the importance of their accurate computation. This paper is concerned with computing LPC coefficients using evolutionary algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Dif-ferential Evolution (DE) and Particle Swarm Optimization with Differentially perturbed Velocity (PSO-DV...
متن کاملA Two-Tier Estimation of Distribution Algorithm for Composite Laminate Optimization
The paper proposes a new evolutionary algorithm for composite laminate optimization, named Double-Distribution Optimization Algorithm (DDOA). DDOA belongs to the family of estimation of distributions algorithms (EDA) that build a statistical model of promising regions of the design space based on sets of good points, and use it to guide the search. A generic framework for introducing statistica...
متن کاملOptimization of sediment rating curve coefficients using evolutionary algorithms and unsupervised artificial neural network
Sediment rating curve (SRC) is a conventional and a common regression model in estimating suspended sediment load (SSL) of flow discharge. However, in most cases the data log-transformation in SRC models causing a bias which underestimates SSL prediction. In this study, using the daily stream flow and suspended sediment load data from Shalman hydrometric station on Shalmanroud River, Guilan Pro...
متن کاملMulti-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms
Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...
متن کاملOPTIMAL CONSTRAINED DESIGN OF STEEL STRUCTURES BY DIFFERENTIAL EVOLUTIONARY ALGORITHMS
Structural optimization, when approached by conventional (gradient based) minimization algorithms presents several difficulties, mainly related to computational aspects for the huge number of nonlinear analyses required, that regard both Objective Functions (OFs) and Constraints. Moreover, from the early '80s to today's, Evolutionary Algorithms have been successfully developed and applied as a ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1999