Computing feasible points for binary MINLPs with MPECs

DOI10.1007/s12532-018-0141-xzbMath1411.90008OpenAlexW2888211270WikidataQ129342618 ScholiaQ129342618MaRDI QIDQ1741127

Lars Schewe, Martin Schmidt

Publication date: 3 May 2019

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

Full work available at URL: https://doi.org/10.1007/s12532-018-0141-x

zbMATH Keywords

complementarity constraintsMPECMINLPmixed-integer nonlinear optimizationprimal heuristic

Mathematics Subject Classification ID

Mixed integer programming (90C11) Nonconvex programming, global optimization (90C26) Approximation methods and heuristics in mathematical programming (90C59) Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) (90C33) Computational methods for problems pertaining to operations research and mathematical programming (90-08)

Related Items

Solving binary-constrained mixed complementarity problems using continuous reformulations ⋮ Complementarity-based nonlinear programming techniques for optimal mixing in gas networks ⋮ Maximizing the storage capacity of gas networks: a global MINLP approach

Uses Software

• BARON
• SCIP
• SNOPT
• CONOPT
• MIPLIB
• FEASPUMP
• Ipopt
• LocalSolver
• GAMS
• MINLPLib

Cites Work

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