Strengthening the sequential convex MINLP technique by perspective reformulations

DOI10.1007/s11590-018-1360-9zbMath1426.90203OpenAlexW2900884495WikidataQ118165410 ScholiaQ118165410MaRDI QIDQ2311102

Claudio Gentile, Claudia D'Ambrosio, Antonio Frangioni

Publication date: 10 July 2019

Published in: Optimization Letters (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11568/935194

zbMATH Keywords

global optimizationperspective reformulationnonconvex separable functionssequential convex MINLP technique

Mathematics Subject Classification ID

Mixed integer programming (90C11) Nonconvex programming, global optimization (90C26)

Uses Software

• SCIP
• CPLEX
• Bonmin
• MINOTAUR

Cites Work

• Approximated perspective relaxations: a project and lift approach
• Minotaur: a mixed-integer nonlinear optimization toolkit
• Improving the approximated projected perspective reformulation by dual information
• A library for continuous convex separable quadratic knapsack problems
• Perspective cuts for a class of convex 0-1 mixed integer programs
• Projected Perspective Reformulations with Applications in Design Problems
• An Algorithmic Framework for MINLP with Separable Non-Convexity
• Perspective Reformulations of the CTA Problem with L₂ Distances
• A Global-Optimization Algorithm for Mixed-Integer Nonlinear Programs Having Separable Non-convexity