A Partitioned ε-Relaxation Algorithm for Separable Convex
Computational Optimization and Applications - Special issue on computational optimization—a tribute to Olvi Mangasarian, part I
Bundle-based relaxation methods for multicommodity capacitated fixed charge network design
Discrete Applied Mathematics - Special issue on the combinatorial optimization symposium
Semidefinite Relaxations of Fractional Programs via Novel Convexification Techniques
Journal of Global Optimization
Perspective cuts for a class of convex 0–1 mixed integer programs
Mathematical Programming: Series A and B
Covering a line segment with variable radius discs
Computers and Operations Research
0-1 reformulations of the multicommodity capacitated network design problem
Discrete Applied Mathematics
Perspective relaxation of mixed integer nonlinear programs with indicator variables
IPCO'08 Proceedings of the 13th international conference on Integer programming and combinatorial optimization
Demand allocation with latency cost functions
Mathematical Programming: Series A and B
SDP diagonalizations and perspective cuts for a class of nonseparable MIQP
Operations Research Letters
A strong conic quadratic reformulation for machine-job assignment with controllable processing times
Operations Research Letters
A computational comparison of reformulations of the perspective relaxation: SOCP vs. cutting planes
Operations Research Letters
Hi-index | 0.00 |
The perspective relaxation (PR) is a general approach for constructing tight approximations to mixed-integer nonlinear programs (MINLP) with semicontinuous variables. The PR of a MINLP can be formulated either as a mixed-integer second-order cone program (MI-SOCP), provided that the original objective function is SOCP-representable, or as a semi-infinite MINLP. In this paper, we show that under some further assumptions (rather restrictive, but satisfied in several practical applications), the PR of a mixed-integer quadratic program (MIQP) can also be reformulated as a piecewise-quadratic program (QP), ultimately yielding a QP relaxation of roughly the same size of the standard continuous relaxation. Furthermore, if the original problem has some exploitable structure, then this structure is typically preserved in the reformulation, thus allowing the construction of specialized approaches for solving the PR. We report on implementing these ideas on two MIQPs with appropriate structure: a sensor placement problem and a quadratic-cost (single-commodity) network design problem.