A quadratic approximation-based local search operator for handling two equality constraints in continuous optimization problems

Carlos H. Fonseca, Elizabeth Fialho Wanner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This work presents extensions of the general methodology of employing quadratic approximations of the objective function and constraints for handling non-linear equality constraints in single-objective optimization problems. The methodology does not require any extra function evaluation since the quadratic approximations are constructed using only information that would be already obtained in the course of the optimization algorithms. The methodology is coupled with the Real Biased Genetic Algorithm to tackle non-linear single-objective optimization problems with two equality constraints. The modified algorithm is tested with a set of analytical problems. The results show the modified algorithm finds the constrained optima with enhanced precision and faster convergence. Considering that the new technique does not impose any additional cost to the algorithms, it can be stated that the technique is also suitable for costly black-box problems.

Original languageEnglish
Title of host publication2016 IEEE Congress on Evolutionary Computation (CEC)
PublisherIEEE
Pages4911-4917
Number of pages7
ISBN (Electronic)978-1-5090-0622-9
DOIs
Publication statusPublished - 14 Nov 2016
Event2016 IEEE Congress on Evolutionary Computation - Vancouver, Canada
Duration: 24 Jul 201629 Jul 2016

Congress

Congress2016 IEEE Congress on Evolutionary Computation
Abbreviated titleCEC 2016
CountryCanada
CityVancouver
Period24/07/1629/07/16

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Quadratic Approximation
Continuous Optimization
Equality Constraints
Local Search
Mathematical operators
Optimization Problem
Methodology
Operator
Nonlinear Constraints
Evaluation Function
Black Box
Biased
Function evaluation
Optimization Algorithm
Objective function
Genetic Algorithm
Genetic algorithms
Costs

Bibliographical note

-

Cite this

Fonseca, Carlos H. ; Wanner, Elizabeth Fialho. / A quadratic approximation-based local search operator for handling two equality constraints in continuous optimization problems. 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. pp. 4911-4917
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Fonseca, CH & Wanner, EF 2016, A quadratic approximation-based local search operator for handling two equality constraints in continuous optimization problems. in 2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, pp. 4911-4917, 2016 IEEE Congress on Evolutionary Computation, Vancouver, Canada, 24/07/16. https://doi.org/10.1109/CEC.2016.7744420

A quadratic approximation-based local search operator for handling two equality constraints in continuous optimization problems. / Fonseca, Carlos H.; Wanner, Elizabeth Fialho.

2016 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2016. p. 4911-4917.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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