A parallel algorithm for partially separable non-convex global minimization: Linear constraints

DOI10.1007/BF02283689zbMath0723.90063OpenAlexW2093694358MaRDI QIDQ2276880

J. Ben Rosen, A. T. Phillips

Publication date: 1990

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02283689

zbMATH Keywords

Branch and boundparallel branch and boundconvex underestimating functionlarge-scale partially separable non-convex problems

Mathematics Subject Classification ID

Convex programming (90C25) Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Nonlinear programming (90C30) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items

Decomposition branch and bound method for globally solving linearly constrained indefinite quadratic minimization problems, New formulations of the multiple sequence alignment problem, Subdomain separability in global optimization, Global optimization of fractional programs, Sufficient conditions for solving linearly constrained separable concave global minimization problems, A continuous approch for globally solving linearly constrained quadratic, Parallel computing in nonconvex programming

Cites Work

• Active constraints, indefinite quadratic test problems, and complexity
• A parallel algorithm for constrained concave quadratic global minimization
• Anomalous Acceleration in Parallel Multiple-Cost-Row Linear Programming
• Error Analysis for Convex Separable Programs: The Piecewise Linear Approximation and The Bounds on The Optimal Objective Value
• An Algorithm for Separable Nonconvex Programming Problems
• An Algorithm for Separable Nonconvex Programming Problems II: Nonconvex Constraints
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