Comparison of Simulated Annealing, Interval Partitioning and Hybrid Algorithms in Constrained Global Optimization

DOI10.1007/978-3-540-72960-0_1zbMath1207.90101OpenAlexW1579890858MaRDI QIDQ3509411

Chandra Sekhar Pedamallu, Linet Özdamar

Publication date: 1 July 2008

Published in: Natural Computing Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-540-72960-0_1

zbMATH Keywords

interval arithmeticpenalty functionfeasible solutionhybrid algorithmconstraint optimization problem

Mathematics Subject Classification ID

Quadratic programming (90C20) Approximation methods and heuristics in mathematical programming (90C59)

Uses Software

• CONOPT
• CFSQP
• INTOPT_90

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• Depth-first iterative-deepening: An optimal admissible tree search
• Global optimization and simulated annealing
• An analytical approach to global optimization
• A collection of test problems for constrained global optimization algorithms
• An interval algorithm for constrained global optimization
• Rigorous global search: continuous problems
• Experiments with new stochastic global optimization search techniques
• Handbook of global optimization. Vol. 2
• Derivative-free filter simulated annealing method for constrained continuous global optimization
• Investigating a hybrid simulated annealing and local search algorithm for constrained optimization
• New interval methods for constrained global optimization
• A set of geometric programming test problems and their solutions
• Subdivision Direction Selection in Interval Methods for Global Optimization
• On Finitely Terminating Branch-and-Bound Algorithms for Some Global Optimization Problems
• Parallel simulated annealing for structural optimization
• Interior Methods for Nonlinear Optimization
• Single and multiobjective structural optimization in discrete‐continuous variables using simulated annealing
• An SQP Algorithm for Finely Discretized Continuous Minimax Problems and Other Minimax Problems with Many Objective Functions
• Global Optimization and Constraint Satisfaction

This page was built for publication: Comparison of Simulated Annealing, Interval Partitioning and Hybrid Algorithms in Constrained Global Optimization