A novel genetic algorithm based method for solving continuous nonlinear optimization problems through subdividing and labeling

[Display omitted] •We introduce a novel algorithm (SLGA) to solve continuous nonlinear optimization problems.•SLGA defines an integer label on a polytope built on a n-dimensional search space.•SLGA applies a crossover operator to approach the optimum by reducing the search space.•New population is g...

Full description

Saved in:

Bibliographic Details
Published in:	Measurement : journal of the International Measurement Confederation Vol. 115; pp. 27 - 38
Main Authors:	Esmaelian, Majid, Tavana, Madjid, Santos-Arteaga, Francisco J., Vali, Masoumeh
Format:	Journal Article
Language:	English
Published:	London Elsevier Ltd 01.02.2018 Elsevier Science Ltd
Subjects:	Combinatorial analysis Continuity (mathematics) Evolutionary algorithms Fitness function Genetic algorithm (GA) Genetic algorithms Iterative methods Labeling Mathematical analysis Nonlinear equations Nonlinear optimization Operators (mathematics) Optimization Optimization algorithms Studies Subdividing labeling Genetic algorithm (GA) Subdividing labeling Fitness function Nonlinear optimization
ISSN:	0263-2241, 1873-412X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!