A Filter-Based Evolutionary Algorithm for Constrained Optimization

We introduce a filter-based evolutionary algorithm (FEA) for constrained optimization. The filter used by an FEA explicitly imposes the concept of dominance on a partially ordered solution set. We show that the algorithm is provably robust for both linear and nonlinear problems and constraints. FEAs use a finite pattern of mutation offsets, and our analysis is closely related to recent convergence results for pattern search methods. We discuss how properties of this pattern impact the ability of an FEA to converge to a constrained local optimum.

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An evolutionary algorithm based pattern search approach for constrained optimization

2013 IEEE Congress on Evolutionary Computation ◽

10.1109/cec.2013.6557722 ◽

2013 ◽

Cited By ~ 4

Author(s):

Rituparna Datta ◽

Kalyanmoy Deb ◽

M. Fernanda P. Costa ◽

A. Gaspar-Cunha

Keyword(s):

Constrained Optimization ◽

Evolutionary Algorithm ◽

Pattern Search ◽

Search Approach

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Generalized pattern search methods for linearly equality constrained optimization problems

Applied Mathematics and Computation ◽

10.1016/j.amc.2005.12.065 ◽

2006 ◽

Vol 181 (1) ◽

pp. 527-535 ◽

Cited By ~ 11

Author(s):

LiYing Liu ◽

XueSheng Zhang

Keyword(s):

Constrained Optimization ◽

Optimization Problems ◽

Pattern Search ◽

Constrained Optimization Problems ◽

Search Methods ◽

Generalized Pattern Search ◽

Equality Constrained Optimization ◽

Pattern Search Methods

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Study of Convergence of Reduced Differential Transform Method for Different Classes of Differential Equations

International Journal of Differential Equations ◽

10.1155/2021/6696414 ◽

2021 ◽

Vol 2021 ◽

pp. 1-16

Author(s):

Seyyedeh Roodabeh Moosavi Noori ◽

Nasir Taghizadeh

Keyword(s):

Differential Equations ◽

Nonlinear Differential Equations ◽

Nonlinear Problems ◽

Differential Transform Method ◽

System Of Differential Equations ◽

Transform Method ◽

Convergence Results ◽

Differential Transform ◽

Linear And Nonlinear ◽

Reduced Differential Transform Method

In this work, we study the sufficient condition for convergence of the reduced differential transform method for nonlinear differential equations. The main power of this method is its ability and flexibility in solving linear and nonlinear problems properly and easily and obtain solutions both numerically and analytically. Simple approaches of reduced differential transform method and the convergence results for different classes of differential equations such as linear and nonlinear ordinary, partial, fractional, and system of differential equations are briefly discussed. Eight examples are checked to confirm convergence results as well as the strength and efficiency of the method.

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