A line up evolutionary algorithm for solving nonlinear constrained optimization problems

DOI10.1016/j.cor.2003.11.015zbMath1122.90433OpenAlexW2019602720MaRDI QIDQ1764763

Haralambos Sarimveis, Athanassios Nikolakopoulos

Publication date: 22 February 2005

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2003.11.015

zbMATH Keywords

Nonlinear programmingConstrained optimizationEvolutionary algorithmsPenalty adaptation

Mathematics Subject Classification ID

Nonlinear programming (90C30) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (5)

A single component mutation evolutionary programming ⋮ An improved simulated annealing for solving the linear constrained optimization problems ⋮ Stochastic radial basis function algorithms for large-scale optimization involving expensive black-box objective and constraint functions ⋮ Multi-operator based evolutionary algorithms for solving constrained optimization problems ⋮ Solving constrained optimization problems using a novel genetic algorithm

Uses Software

• Genocop

Cites Work

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• Genetic algorithms and very fast simulated reannealing: A comparison
• Simulated annealing: Practice versus theory
• A hybrid genetic algorithm for a type of nonlinear programming problem
• Genetic Algorithms for Combinatorial Optimization: The Assemble Line Balancing Problem
• Adaptive Penalty Methods for Genetic Optimization of Constrained Combinatorial Problems
• Extension of a hybrid genetic algorithm for nonlinear programming problems with equality and inequality constraints.

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