Rounding-based heuristics for nonconvex MINLPS

DOI10.1007/s12532-011-0032-xzbMath1257.90059OpenAlexW1991970232MaRDI QIDQ1762458

Giacomo Nannicini, Pietro Belotti

Publication date: 27 November 2012

Published in: Mathematical Programming Computation (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/1721.1/105215

zbMATH Keywords

improved solutioninitial feasible solutionnonconvex mixed-integer nonlinear programs

Mathematics Subject Classification ID

Mixed integer programming (90C11) Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Approximation methods and heuristics in mathematical programming (90C59)

Related Items

Three ideas for a feasibility pump for nonconvex MINLP, Global optimization advances in mixed-integer nonlinear programming, MINLP, and constrained derivative-free optimization, CDFO, Mixed integer nonlinear programming tools: an updated practical overview, Guided dive for the spatial branch-and-bound, A recipe for finding good solutions to MINLPs, A storm of feasibility pumps for nonconvex MINLP, On interval-subgradient and no-good cuts, A feasible rounding approach for mixed-integer optimization problems, A partial outer convexification approach to control transmission lines, On the statistical evaluation of algorithmic's computational experimentation with infeasible solutions, Multidimensional sum-up rounding for integer programming in optimal experimental design, Measuring the impact of primal heuristics, Undercover: a primal MINLP heuristic exploring a largest sub-MIP, Computing feasible points for binary MINLPs with MPECs, A computational study of primal heuristics inside an MI(NL)P solver, Water distribution networks design under uncertainty, Rounding-based heuristics for nonconvex MINLPS, A primal heuristic for optimizing the topology of gas networks based on dual information, RENS. The optimal rounding, Mixed integer nonlinear programming tools: a practical overview

Uses Software

• BARON
• CPLEX
• Couenne
• LINDO
• FEASPUMP
• Ipopt
• MINLPLib

Cites Work

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