The structure of the infinite models in integer programming

Size: px
Start display at page:

Download "The structure of the infinite models in integer programming"

Transcription

1 The structure of the infinite models in integer programming January 10, 2017

2 Not Again! Well, Aussois is partly responsible... Some years ago:

3 Not Again! Well, Aussois is partly responsible... Some years ago: Tuesday, January 8, 2008 Chair: Laurence Wolsey 17:15-18:00 Jean-Philippe Richard Group Relaxations for Integer Programming 18:00-18:30 Santanu Dey Facets of High-Dimensional Infinite Group Problem

4 Not Again! Well, Aussois is partly responsible... Some years ago: Tuesday, January 8, 2008 Chair: Laurence Wolsey 17:15-18:00 Jean-Philippe Richard Group Relaxations for Integer Programming 18:00-18:30 Santanu Dey Facets of High-Dimensional Infinite Group Problem Jean-Philippe P. Richard, Santanu S. Dey The Group-Theoretic Approach in Mixed Integer Programming: Theory, Computation and Perspectives, Fifty years of Integer Programming : From early years to the state-of-the-art (M. Juenger, T. Liebling, D. Naddef, G. Nemhauser, W. Pulleyblank, G. Reinelt, G. Rinaldi, and L. Wolsey (eds.)), December 2009 (Springer).

5 Not Again! Well, Aussois is partly responsible... Some years ago: Tuesday, January 8, 2008 Chair: Laurence Wolsey 17:15-18:00 Jean-Philippe Richard Group Relaxations for Integer Programming 18:00-18:30 Santanu Dey Facets of High-Dimensional Infinite Group Problem Jean-Philippe P. Richard, Santanu S. Dey The Group-Theoretic Approach in Mixed Integer Programming: Theory, Computation and Perspectives, Fifty years of Integer Programming : From early years to the state-of-the-art (M. Juenger, T. Liebling, D. Naddef, G. Nemhauser, W. Pulleyblank, G. Reinelt, G. Rinaldi, and L. Wolsey (eds.)), December 2009 (Springer). a lot of research since then...

6 MIPs in tableau form b R n \Z n. x B + r R rs(r)+ p Ppy(p) = b, x B Z n,s(r) R +,y(p) Z +

7 MIPs in tableau form b R n \Z n. x B + r R rs(r)+ p Ppy(p) = b, x B Z n,s(r) R +,y(p) Z + rs(r)+ p Ppy(p) b +Z n, s(r) R +,y(p) Z + r R

8 MIPs in tableau form b R n \Z n. x B + r R rs(r)+ p Ppy(p) = b, x B Z n,s(r) R +,y(p) Z + rs(r)+ p Ppy(p) b +Z n, s(r) R +,y(p) Z + r R BFS: s(r) = y(p) = 0, x B = b. Want x B Z n

9 The mixed-integer model Mixed-integer infinite group relaxation b R n \Z n, s : R n R + and y : R n Z + M b = {s,y R (Rn ) ) + R(Rn + : rs(r)+ py(p) b +Z n }. r R n p R n R (Rn) is the set of finite support functions from R n to R. R (Rn ) +.

10 The mixed-integer model Mixed-integer infinite group relaxation b R n \Z n, s : R n R + and y : R n Z + M b = {s,y R (Rn ) ) + R(Rn + : rs(r)+ py(p) b +Z n }. r R n p R n R (Rn) is the set of finite support functions from R n to R. R (Rn ) +. (ψ,π,α), ψ,π : R n R, α R, { H ψ,π,α := (s,y) R (Rn) R (Rn) : } ψ(r)s(r)+ π(p)y(p) α r R n p R n (ψ,π,α) is a valid tuple (functions) for M b if M b H ψ,π,α. equivalently: conv(m b ). α { 1,0,1}.

11 A face: The pure integer model The pure integer infinite group relaxation y : R n Z +. I b = {y : (0,y) M b } = {y R (Rn ) + : p R n py(p) b +Z n }.

12 A face: The pure integer model The pure integer infinite group relaxation y : R n Z +. I b = {y : (0,y) M b } = {y R (Rn ) + : p R n py(p) b +Z n }. (π,α), π : R n R, α R, { H π,α := y R (Rn) : } π(p)y(p) α p R n (π,α) is a valid tuple for I b if I b H π,α.

13 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b

14 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1

15 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1 Subadditive if φ(r 1 )+φ(r 2 ) φ(r 1 +r 2 ), r 1,r 2 R n. (ψ, π)

16 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1 Subadditive if φ(r 1 )+φ(r 2 ) φ(r 1 +r 2 ), r 1,r 2 R n. (ψ, π) Positively homogenous if φ(λr) = λφ(r) r R n and λ 0. (ψ)

17 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1 Subadditive if φ(r 1 )+φ(r 2 ) φ(r 1 +r 2 ), r 1,r 2 R n. (ψ, π) Positively homogenous if φ(λr) = λφ(r) r R n and λ 0. (ψ) Sublinear subadditive + positive homogenous. (ψ)

18 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1 Subadditive if φ(r 1 )+φ(r 2 ) φ(r 1 +r 2 ), r 1,r 2 R n. (ψ, π) Positively homogenous if φ(λr) = λφ(r) r R n and λ 0. (ψ) Sublinear subadditive + positive homogenous. (ψ) Periodic φ(r) = φ(r +z), r R n and z Z n.(π)

19 Gomory functions n = 1, α = 1, very simple to describe (0 < b < 1). { r ψ(r) = b if r 0 r 1 b if r < 0 π(p) = { f(p) b 1 f(p) 1 b if f(p) b if f(p) > b 1 1 b b 1 Subadditive if φ(r 1 )+φ(r 2 ) φ(r 1 +r 2 ), r 1,r 2 R n. (ψ, π) Positively homogenous if φ(λr) = λφ(r) r R n and λ 0. (ψ) Sublinear subadditive + positive homogenous. (ψ) Periodic φ(r) = φ(r +z), r R n and z Z n.(π) Symmetry condition φ satisfies φ(r)+φ(b r) = 1. (π)

20 Attractiveness of valid functions: Plug and play 3.6s s 2 +.2y 1.2y 2 =.4+Z s 1,s 2 R +,y 1,y 2 Z +

21 Attractiveness of valid functions: Plug and play 3.6s s 2 +.2y 1.2y 2 =.4+Z s 1,s 2 R +,y 1,y 2 Z +...not so easy as it seems, but attractive nevertheless.

22 Attractiveness of valid functions: Plug and play 3.6s s 2 +.2y 1.2y 2 =.4+Z s 1,s 2 R +,y 1,y 2 Z +...not so easy as it seems, but attractive nevertheless....library of useful functions in IP solvers.

23 What are the important functions? What should we put in our library?

24 What are the important functions? What should we put in our library? Nontrivial: Not valid for R (Rn ) ) + R(Rn +. Minimal: Undominated in R (Rn ) ) + R(Rn +. Extreme: Later. Facet: Later.

25 What are the important functions? What should we put in our library? Nontrivial: Not valid for R (Rn ) ) + R(Rn +. Minimal: Undominated in R (Rn ) ) + R(Rn +. Extreme: Later. Facet: Later. A (seemingly) technical detour: π 0 Why? There are minimal functions π 0, but they are pathological: Every disc contains some (x,f(x)).

26 What are the important functions? What should we put in our library? Nontrivial: Not valid for R (Rn ) ) + R(Rn +. Minimal: Undominated in R (Rn ) ) + R(Rn +. Extreme: Later. Facet: Later. A (seemingly) technical detour: π 0 Why? There are minimal functions π 0, but they are pathological: Every disc contains some (x,f(x))....but ignorance should not be an excuse... We try to answer this.

27 What are the important functions? Theorem (Yildiz and Cornuéjols, related to Johnson.) Let ψ : R n R, π : R n R be any functions, and α { 1,0,1}. Then (ψ,π,α) is a nontrivial minimal valid tuple for M b if and only if: π is subadditive; π(ǫr) ψ(r) = sup ǫ>0 ǫ = lim π(ǫr) ǫ 0 + ǫ = limsup π(ǫr) ǫ 0 + ǫ every r R n ; sublinear π is Lipschitz continuous with Lipschitz constant L := max r =1 ψ(r); π 0, π(z) = 0 for every z Z n, and α = 1; π satisfies the symmetry condition (and is periodic). for

28 (One of our) Goal(s) Q b = R (Rn ) ) + R(Rn + = R (Rn ) ) + R(Rn + H ψ,π,α (ψ,π,α) valid (ψ,π,α) minimal, nontrivial H ψ,π,α

29 (One of our) Goal(s) Q b = R (Rn ) ) + R(Rn + = R (Rn ) ) + R(Rn + H ψ,π,α (ψ,π,α) valid (ψ,π,α) minimal, nontrivial H ψ,π,α Clearly conv(m b ) Q b. But what is Q b?

30 Norms, closed sets... While in finite dimensions all norms are equivalent to the Euclidean norm, In infinite dimensions this is not so... Norm on R (Rn) R (Rn) (BCCZ): (s,y) := s(0) + r s(r) + y(0) + p y(p) r R n p R n

31 Norms, closed sets... While in finite dimensions all norms are equivalent to the Euclidean norm, In infinite dimensions this is not so... Norm on R (Rn) R (Rn) (BCCZ): (s,y) := s(0) + r s(r) + y(0) + p y(p) r R n p R n Theorem Under the topology induced by (, ), Q b = cl(conv(m b )) = conv(m b )+R (Rn ) + R(Rn ) +.

32 Norms, closed sets... While in finite dimensions all norms are equivalent to the Euclidean norm, In infinite dimensions this is not so... Norm on R (Rn) R (Rn) (BCCZ): (s,y) := s(0) + r s(r) + y(0) + p y(p) r R n p R n Theorem Under the topology induced by (, ), Q b = cl(conv(m b )) = conv(m b )+R (Rn ) + R(Rn ) +. conv(m b ) conv(m b )+R (Rn ) + R(Rn )

33 Liftable functions G b = {y R (Rn) : (0,y) Q b } (Minimal, nontrivial) (π,α) valid for I b liftable if ψ s.t. (ψ,π,α) (Minimal, nontrivial) valid for M b. G b = R (Rn ) + {H π,α : (π,α) minimal nontrivial liftable tuple}.

34 Liftable functions G b = {y R (Rn) : (0,y) Q b } (Minimal, nontrivial) (π,α) valid for I b liftable if ψ s.t. (ψ,π,α) (Minimal, nontrivial) valid for M b. G b = R (Rn ) + {H π,α : (π,α) minimal nontrivial liftable tuple}. Theorem G b = cl(conv(i b )) = conv(i b )+R (Rn ) +.

35 Liftable functions G b = {y R (Rn) : (0,y) Q b } (Minimal, nontrivial) (π,α) valid for I b liftable if ψ s.t. (ψ,π,α) (Minimal, nontrivial) valid for M b. G b = R (Rn ) + {H π,α : (π,α) minimal nontrivial liftable tuple}. Theorem G b = cl(conv(i b )) = conv(i b )+R (Rn ) +. conv(i b ) conv(i b )+R (Rn ) +

36 Canonical faces, Finite faces Ultimately we want valid inequalities for Integer Programs (with rational data). Given R,P R n, let V R,P = { (s,y) R (Rn) R (Rn) : s(r) = 0 r R, y(p) = 0 p P }. A canonical face of conv(m b ) is F = conv(m b ) V R,P. When R, P finite, F is a finite canonical face.

37 Canonical faces, Finite faces Ultimately we want valid inequalities for Integer Programs (with rational data). Given R,P R n, let V R,P = { (s,y) R (Rn) R (Rn) : s(r) = 0 r R, y(p) = 0 p P }. A canonical face of conv(m b ) is F = conv(m b ) V R,P. When R, P finite, F is a finite canonical face. Notice: conv(m b ) = F finite canonical face

38 Canonical faces, Finite faces Ultimately we want valid inequalities for Integer Programs (with rational data). Given R,P R n, let V R,P = { (s,y) R (Rn) R (Rn) : s(r) = 0 r R, y(p) = 0 p P }. A canonical face of conv(m b ) is F = conv(m b ) V R,P. When R, P finite, F is a finite canonical face. Notice: conv(m b ) = F finite canonical face Same for conv(i b ). Finite canonical faces of conv(i b ) are the corner polyhedra.

39 Rational finite faces What happens when R, P Q n? Theorem Let R,P Q n. Then conv(m b ) V R,P = cl(conv(m b )) V R,P. Let P Q n. Then conv(i b ) V P = cl(conv(i b )) V P. Corollary The restrictions of the minimal, nontrivial valid tuples give all the (nontrivial) facets of rational mixed-integer polyhedra. The restrictions of the minimal, nontrivial liftable functions give all the (nontrivial) facets of rational corner polyhedra,

40 Extreme functions and facets π 0 extreme if (π,1) valid and π 1 = π 2 = π for every π 1 0, π 2 0 such that (π 1,1) (π 2,1) valid and π = 1 2 π π 2. π 0 facet if (π,1) valid and π 1 = π for every π 1 0, such that H π1,1 I b H π1,1 I b. π facet π extreme. The converse is not known. Köppe and Zhou: Coincide for the case of continuous piecewise linear functions On the notions of facets, weak facets, and extreme functions of the Gomory-Johnson infinite group problem n = 1, software to test extremality of piecewise linear functions.

41 Discontinuous extreme functions (n = 1) Dey, Richard, Li and Miller: The following function is extreme: n = 1, 0 < b < 1 2, π : π(r) = { r b 0 r b r 1+b b < r < 1 1 b 1

42 More discontinuous functions (n = 1) Letchford, Lodi Strong fractional functions Minimal, dominate fractional functions. Dash, Günlük Extended two-step MIR (mixed integer rounding) functions. limit of sequences of two-step MIR functions, dominate LetcLo. Hildebrand, two-sided discontinuous at the origin with 1 or 2 slopes, extreme Köppe, Zhou: Extreme functions that are continuous but not Lipschitz continuous. see Köppe, Zhou Equivariant perturbation in Gomory and Johnson s infinite group problem. vi. the curious case of two-sided discontinuous functions.

43 Not all extreme functions are needed Summarizing our results: cl(conv(i b )) = conv(i b )+R (Rn ) + = = R (Rn ) + {H π,α : (π,α) minimal nontrivial liftable tuple}. When P Q n, we have that cl(conv(i b )) V P = conv(i b ) V P (π,α) minimal nontrivial liftable tuple: π 0, α = 1, π Lipschitz continuous. ONLY THESE ARE NEEDED

44 Cauchy equation and Hamel bases The Cauchy functional equation in R n : θ(u)+θ(v) = θ(u +v) for all u,v R n. (subadditivity) θ(x) = c T x is obviously a solution to the equation. A Hamel basis B in a basis of R n over the field Q. i.e. a subset of R n s.t. x R n, there exists a unique finite subset {β 1,...,β t } B and λ 1,...,λ t Q such that x = t i=1 λ iβ i. (axiom of choice).

45 Cauchy equation and Hamel bases II For β B, let c(β) R be a real number. Define θ as:...θ solves the Cauchy equation. θ(x) = t i=1 λ ic(β i ). Theorem Let B a Hamel basis of R n. Then every solution to the Cauchy equation is of this form.

46 The affine hull of conv(i b ) Theorem (Basu, Hildebrand Köppe) The affine hull of conv(i b ) is described by the equations p Rn θ(p)y(p) = θ(b) for all solutions θ : R n R of the Cauchy equation such that θ(p) = 0 for every p Q n. Extreme functions (without π 0) do not exist... aff(cl(conv(i b ))) = R (Rn ) aff(conv(m b )) = aff(cl(conv(m b ))) = R (Rn) R (Rn).

47 Every valid function is nonnegative. Theorem For every valid tuple (π,α) for I b, there exists a unique solution of the Cauchy equation θ : R n R such that θ(p) = 0 for every p Q n and the valid tuple (π,α ) = (π +θ,α+θ(b)) satisfies π 0. Nonnegative valid functions form a compact, convex set. Its extreme points are the extreme functions and suffice to describe this set. (...but not all of them are necessary)

48 Finite faces and recession cones 2y1.2y 2 +(1 2)y 3.4+Z y 1,y 2,y 3 Z + y 1 = y 3, (1,0,1)

49 Finite faces and recession cones 2y1.2y 2 +(1 2)y 3.4+Z y 1,y 2,y 3 Z + y 1 = y 3, (1,0,1) L the linear space parallel to aff(conv(i b )) Theorem For every P R n finite: the face C P = conv(i b ) V P is a rational polyhedron in R P ; every extreme ray of C P is spanned by some r Z P + such that p P pr(p) Zn ; rec(c P ) = (L V P ) R P +.

50 Finite faces and recession cones Theorem There are finite canonical faces of conv(m b ) that are not closed. All the finite canonical faces of conv(i b ) are rational polyhedra.

51 More work? n = 1: EVERY EXTREME FUNCTION π 0 IS NICE. Gomory Johnson: Every extreme function is piecewise linear. NO Basu, Conforti, Cornuejols, Zambelli.

52 More work? n = 1: EVERY EXTREME FUNCTION π 0 IS NICE. Gomory Johnson: Every extreme function is piecewise linear. NO Basu, Conforti, Cornuejols, Zambelli. Dey and Richard Aussois 2008 Construct extreme functions that are piecewise linear and have > 4 slopes. YES Hildebrand (2013) 6 Köppe and Zhou (2015) 28. Computer search. BCDP (2015) For every k there exists an extreme function that is piecewise linear with k slopes. The pointwise limit of this sequence is extreme with slopes.

53 More work? n = 1: EVERY EXTREME FUNCTION π 0 IS NICE. Gomory Johnson: Every extreme function is piecewise linear. NO Basu, Conforti, Cornuejols, Zambelli. Dey and Richard Aussois 2008 Construct extreme functions that are piecewise linear and have > 4 slopes. YES Hildebrand (2013) 6 Köppe and Zhou (2015) 28. Computer search. BCDP (2015) For every k there exists an extreme function that is piecewise linear with k slopes. The pointwise limit of this sequence is extreme with slopes. Is every bad function (discontinuous, non piecewise linear, slopes) the pointwise limit of a sequence of good functions?

54 Maybe nice functions suffice... Is every facet of conv(i b ) V P, P finite (rational) the restriction of a piecewise linear function?

55 Maybe nice functions suffice... Is every facet of conv(i b ) V P, P finite (rational) the restriction of a piecewise linear function? conv(i b ) = cl(conv(i b )) aff(conv(i b ))?

56 THANK YOU FOR YOUR ATTENTION

57

The Strength of Multi-row Aggregation Cuts for Sign-pattern Integer Programs

The Strength of Multi-row Aggregation Cuts for Sign-pattern Integer Programs The Strength of Multi-row Aggregation Cuts for Sign-pattern Integer Programs Santanu S. Dey 1, Andres Iroume 1, and Guanyi Wang 1 1 School of Industrial and Systems Engineering, Georgia Institute of Technology

More information

A Lower Bound on the Split Rank of Intersection Cuts

A Lower Bound on the Split Rank of Intersection Cuts A Lower Bound on the Split Rank of Intersection Cuts Santanu S. Dey H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology. 200 Outline Introduction: split rank,

More information

Convex Sets and Minimal Sublinear Functions

Convex Sets and Minimal Sublinear Functions Convex Sets and Minimal Sublinear Functions Amitabh Basu Gérard Cornuéjols Giacomo Zambelli April 2010 Abstract We show that, given a closed convex set K containing the origin in its interior, the support

More information

Some cut-generating functions for second-order conic sets

Some cut-generating functions for second-order conic sets Some cut-generating functions for second-order conic sets Asteroide Santana 1 and Santanu S. Dey 1 1 School of Industrial and Systems Engineering, Georgia Institute of Technology June 1, 2016 Abstract

More information

Corner Polyhedron and Intersection Cuts

Corner Polyhedron and Intersection Cuts Corner Polyhedron and Intersection Cuts Michele Conforti 1,5, Gérard Cornuéjols 2,4 Giacomo Zambelli 3,5 August 2010 Revised March 2011 Abstract Four decades ago, Gomory introduced the corner polyhedron

More information

Minimal Valid Inequalities for Integer Constraints

Minimal Valid Inequalities for Integer Constraints Minimal Valid Inequalities for Integer Constraints Valentin Borozan LIF, Faculté des Sciences de Luminy, Université de Marseille, France borozan.valentin@gmail.com and Gérard Cornuéjols Tepper School of

More information

Mixing Inequalities and Maximal Lattice-Free Triangles

Mixing Inequalities and Maximal Lattice-Free Triangles Mixing Inequalities and Maximal Lattice-Free Triangles Santanu S. Dey Laurence A. Wolsey Georgia Institute of Technology; Center for Operations Research and Econometrics, UCL, Belgium. 2 Outline Mixing

More information

Minimal inequalities for an infinite relaxation of integer programs

Minimal inequalities for an infinite relaxation of integer programs Minimal inequalities for an infinite relaxation of integer programs Amitabh Basu Carnegie Mellon University, abasu1@andrew.cmu.edu Michele Conforti Università di Padova, conforti@math.unipd.it Gérard Cornuéjols

More information

Minimal inequalities for an infinite relaxation of integer programs

Minimal inequalities for an infinite relaxation of integer programs Minimal inequalities for an infinite relaxation of integer programs Amitabh Basu Carnegie Mellon University, abasu1@andrew.cmu.edu Michele Conforti Università di Padova, conforti@math.unipd.it Gérard Cornuéjols

More information

Equivariant Perturbation in Gomory and Johnson s Infinite Group Problem. I. The One-Dimensional Case

Equivariant Perturbation in Gomory and Johnson s Infinite Group Problem. I. The One-Dimensional Case Equivariant Perturbation in Gomory and Johnson s Infinite Group Problem. I. The One-Dimensional Case Amitabh Basu Robert Hildebrand Matthias Köppe March 25, 204 Abstract We give an algorithm for testing

More information

A geometric perspective on lifting

A geometric perspective on lifting A geometric perspective on lifting Michele Conforti Università di Padova, conforti@math.unipd.it Gérard Cornuéjols Carnegie Mellon University and Université d Aix-Marseille, gc0v@andrew.cmu.edu Giacomo

More information

The Split Closure of a Strictly Convex Body

The Split Closure of a Strictly Convex Body The Split Closure of a Strictly Convex Body D. Dadush a, S. S. Dey a, J. P. Vielma b,c, a H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive

More information

The Split Closure of a Strictly Convex Body

The Split Closure of a Strictly Convex Body The Split Closure of a Strictly Convex Body D. Dadush a, S. S. Dey a, J. P. Vielma b,c, a H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive

More information

On the Relative Strength of Split, Triangle and Quadrilateral Cuts

On the Relative Strength of Split, Triangle and Quadrilateral Cuts On the Relative Strength of Split, Triangle and Quadrilateral Cuts Amitabh Basu Pierre Bonami Gérard Cornuéjols François Margot Abstract Integer programs defined by two equations with two free integer

More information

Multi-Row Cuts in Integer Programming. Tepper School of Business Carnegie Mellon University, Pittsburgh

Multi-Row Cuts in Integer Programming. Tepper School of Business Carnegie Mellon University, Pittsburgh Multi-Row Cuts in Integer Programming Gérard Cornuéjols Tepper School o Business Carnegie Mellon University, Pittsburgh March 2011 Mixed Integer Linear Programming min s.t. cx Ax = b x j Z or j = 1,...,

More information

Approximation of Minimal Functions by Extreme Functions

Approximation of Minimal Functions by Extreme Functions Approximation of Minimal Functions by Extreme Functions Teresa M. Lebair and Amitabh Basu August 14, 2017 Abstract In a recent paper, Basu, Hildebrand, and Molinaro established that the set of continuous

More information

Some Relationships between Disjunctive Cuts and Cuts based on S-free Convex Sets

Some Relationships between Disjunctive Cuts and Cuts based on S-free Convex Sets Some Relationships between Disjunctive Cuts and Cuts based on S-free Convex Sets Sanjeeb Dash a Santanu S. Dey b Oktay Günlük a a Business Analytics and Mathematical Sciences Department, IBM T. J. Watson

More information

Polyhedral Approach to Integer Linear Programming. Tepper School of Business Carnegie Mellon University, Pittsburgh

Polyhedral Approach to Integer Linear Programming. Tepper School of Business Carnegie Mellon University, Pittsburgh Polyhedral Approach to Integer Linear Programming Gérard Cornuéjols Tepper School of Business Carnegie Mellon University, Pittsburgh 1 / 30 Brief history First Algorithms Polynomial Algorithms Solving

More information

Structure in Mixed Integer Conic Optimization: From Minimal Inequalities to Conic Disjunctive Cuts

Structure in Mixed Integer Conic Optimization: From Minimal Inequalities to Conic Disjunctive Cuts Structure in Mixed Integer Conic Optimization: From Minimal Inequalities to Conic Disjunctive Cuts Fatma Kılınç-Karzan Tepper School of Business Carnegie Mellon University Joint work with Sercan Yıldız

More information

A geometric perspective on lifting

A geometric perspective on lifting A geometric perspective on lifting Michele Conforti Università di Padova, conforti@math.unipd.it Gérard Cornuéjols Carnegie Mellon University and Université d Aix-Marseille, gc0v@andrew.cmu.edu Giacomo

More information

Structure of Valid Inequalities for Mixed Integer Conic Programs

Structure of Valid Inequalities for Mixed Integer Conic Programs Structure of Valid Inequalities for Mixed Integer Conic Programs Fatma Kılınç-Karzan Tepper School of Business Carnegie Mellon University 18 th Combinatorial Optimization Workshop Aussois, France January

More information

A geometric approach to cut-generating functions

A geometric approach to cut-generating functions A geometric approach to cut-generating functions Amitabh Basu Michele Conforti Marco Di Summa February 18, 2015 Abstract The cutting-plane approach to integer programming was initiated more that 40 years

More information

1 Solution of a Large-Scale Traveling-Salesman Problem... 7 George B. Dantzig, Delbert R. Fulkerson, and Selmer M. Johnson

1 Solution of a Large-Scale Traveling-Salesman Problem... 7 George B. Dantzig, Delbert R. Fulkerson, and Selmer M. Johnson Part I The Early Years 1 Solution of a Large-Scale Traveling-Salesman Problem............ 7 George B. Dantzig, Delbert R. Fulkerson, and Selmer M. Johnson 2 The Hungarian Method for the Assignment Problem..............

More information

On the Relative Strength of Split, Triangle and Quadrilateral Cuts

On the Relative Strength of Split, Triangle and Quadrilateral Cuts On the Relative Strength of Split, Triangle and Quadrilateral Cuts Amitabh Basu Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 53 abasu@andrew.cmu.edu Pierre Bonami LIF, Faculté

More information

On the Relative Strength of Split, Triangle and Quadrilateral Cuts

On the Relative Strength of Split, Triangle and Quadrilateral Cuts On the Relative Strength of Split, Triangle and Quadrilateral Cuts Amitabh Basu Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA 53 abasu@andrew.cmu.edu Pierre Bonami LIF, Faculté

More information

Lifting Integer Variables in Minimal Inequalities Corresponding To Lattice-Free Triangles

Lifting Integer Variables in Minimal Inequalities Corresponding To Lattice-Free Triangles Lifting Integer Variables in Minimal Inequalities Corresponding To Lattice-Free Triangles Santanu S. Dey and Laurence A. Wolsey 2 CORE, 2 CORE and INMA, University Catholique de Louvain, 34, Voie du Roman

More information

Maximal lattice-free convex sets in linear subspaces

Maximal lattice-free convex sets in linear subspaces Maximal lattice-free convex sets in linear subspaces Amitabh Basu Carnegie Mellon University, abasu1@andrew.cmu.edu Michele Conforti Università di Padova, conforti@math.unipd.it Gérard Cornuéjols Carnegie

More information

The master equality polyhedron with multiple rows

The master equality polyhedron with multiple rows The master equality polyhedron with multiple rows Sanjeeb Dash Ricardo Fukasawa IBM Research February 17, 2009 Oktay Günlük Abstract The master equality polyhedron (MEP) is a canonical set that generalizes

More information

Cut-Generating Functions for Integer Variables

Cut-Generating Functions for Integer Variables Cut-Generating Functions for Integer Variables Sercan Yıldız and Gérard Cornuéjols December 204, revised August 205 Abstract For an integer linear program, Gomory s corner relaxation is obtained by ignoring

More information

Sufficiency of Cut-Generating Functions

Sufficiency of Cut-Generating Functions Sufficiency of Cut-Generating Functions Gérard Cornuéjols 1, Laurence Wolsey 2, and Sercan Yıldız 1 1 Tepper School of Business, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA 15213, United

More information

Cutting Planes and Elementary Closures for Non-linear Integer Programming

Cutting Planes and Elementary Closures for Non-linear Integer Programming Cutting Planes and Elementary Closures for Non-linear Integer Programming Juan Pablo Vielma University of Pittsburgh joint work with D. Dadush and S. S. Dey S. Modaresi and M. Kılınç Georgia Institute

More information

Lattice closures of polyhedra

Lattice closures of polyhedra Lattice closures of polyhedra Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Oktay Günlük IBM Research gunluk@us.ibm.com October 27, 2016 Diego A. Morán R. Universidad Adolfo Ibañez diego.moran@uai.cl Abstract

More information

Convex Sets and Minimal Sublinear Functions

Convex Sets and Minimal Sublinear Functions Convex Sets and Minimal Sublinear Functions Amitabh Basu Gérard Cornuéjols Giacomo Zambelli March 2009, revised January 2010 Abstract We show that, given a closed convex set K containing the origin in

More information

Integer Programming ISE 418. Lecture 13. Dr. Ted Ralphs

Integer Programming ISE 418. Lecture 13. Dr. Ted Ralphs Integer Programming ISE 418 Lecture 13 Dr. Ted Ralphs ISE 418 Lecture 13 1 Reading for This Lecture Nemhauser and Wolsey Sections II.1.1-II.1.3, II.1.6 Wolsey Chapter 8 CCZ Chapters 5 and 6 Valid Inequalities

More information

Computing with multi-row Gomory cuts

Computing with multi-row Gomory cuts Computing with multi-row Gomory cuts Daniel G. Espinoza Departamento de Ingeniería Industrial, Universidad de Chile, Av. República 71, Santiago, 837-439, Chile Abstract Recent advances on the understanding

More information

LP Relaxations of Mixed Integer Programs

LP Relaxations of Mixed Integer Programs LP Relaxations of Mixed Integer Programs John E. Mitchell Department of Mathematical Sciences RPI, Troy, NY 12180 USA February 2015 Mitchell LP Relaxations 1 / 29 LP Relaxations LP relaxations We want

More information

THE MIXING SET WITH FLOWS

THE MIXING SET WITH FLOWS THE MIXING SET WITH FLOWS MICHELE CONFORTI, MARCO DI SUMMA, AND LAURENCE A. WOLSEY Abstract. We consider the mixing set with flows: s + x t b t, x t y t for 1 t n; s R 1 +, x Rn +, y Zn +. It models a

More information

The master equality polyhedron with multiple rows

The master equality polyhedron with multiple rows The master equality polyhedron with multiple rows Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Ricardo Fukasawa University of Waterloo rfukasaw@math.uwaterloo.ca September 16, 2010 Oktay Günlük IBM Research

More information

Operations that preserve the covering property of the lifting region

Operations that preserve the covering property of the lifting region Operations that preserve the covering property of the lifting region Amitabh Basu and Joe Paat June 23, 2015 Abstract We contribute to the theory for minimal liftings of cut-generating functions. In particular,

More information

Relations Between Facets of Low- and High-Dimensional Group Problems

Relations Between Facets of Low- and High-Dimensional Group Problems Mathematical Programming manuscript No. (will be inserted by the editor) Santanu S. Dey Jean-Philippe P. Richard Relations Between Facets of Low- and High-Dimensional Group Problems Received: date / Accepted:

More information

Valid inequalities based on simple mixed-integer sets

Valid inequalities based on simple mixed-integer sets Valid inequalities based on simple mixed-integer sets Sanjeeb Dash and Oktay Günlük Mathematical Sciences Department, IBM T J Watson Research Center,Yorktown Heights, NY 10598 (sanjeebd@usibmcom, oktay@watsonibmcom)

More information

Key words. Integer nonlinear programming, Cutting planes, Maximal lattice-free convex sets

Key words. Integer nonlinear programming, Cutting planes, Maximal lattice-free convex sets ON MAXIMAL S-FREE CONVEX SETS DIEGO A. MORÁN R. AND SANTANU S. DEY Abstract. Let S Z n satisfy the property that conv(s) Z n = S. Then a convex set K is called an S-free convex set if int(k) S =. A maximal

More information

A Constructive Characterization of the Split Closure of a Mixed Integer Linear Program. Juan Pablo Vielma

A Constructive Characterization of the Split Closure of a Mixed Integer Linear Program. Juan Pablo Vielma A Constructive Characterization of the Split Closure of a Mixed Integer Linear Program Juan Pablo Vielma June 26, 2006 Review: MIP and Relaxation We study the MIP feasible region P I := {x P R n : x j

More information

Computing with Multi-Row Intersection Cuts

Computing with Multi-Row Intersection Cuts Computing with Multi-Row Intersection Cuts by Álinson Santos Xavier A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics

More information

The Triangle Closure is a Polyhedron

The Triangle Closure is a Polyhedron The Triangle Closure is a Polyhedron Amitabh Basu Robert Hildebrand Matthias Köppe November 7, 21 Abstract Recently, cutting planes derived from maximal lattice-free convex sets have been studied intensively

More information

The Chvátal-Gomory Closure of an Ellipsoid is a Polyhedron

The Chvátal-Gomory Closure of an Ellipsoid is a Polyhedron The Chvátal-Gomory Closure of an Ellipsoid is a Polyhedron Santanu S. Dey 1 and Juan Pablo Vielma 2,3 1 H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology,

More information

Chapter 1. Preliminaries

Chapter 1. Preliminaries Introduction This dissertation is a reading of chapter 4 in part I of the book : Integer and Combinatorial Optimization by George L. Nemhauser & Laurence A. Wolsey. The chapter elaborates links between

More information

Projected Chvátal-Gomory cuts for Mixed Integer Linear Programs. Pierre Bonami CMU, USA. Gerard Cornuéjols CMU, USA and LIF Marseille, France

Projected Chvátal-Gomory cuts for Mixed Integer Linear Programs. Pierre Bonami CMU, USA. Gerard Cornuéjols CMU, USA and LIF Marseille, France Projected Chvátal-Gomory cuts for Mixed Integer Linear Programs Pierre Bonami CMU, USA Gerard Cornuéjols CMU, USA and LIF Marseille, France Sanjeeb Dash IBM T.J. Watson, USA Matteo Fischetti University

More information

Subadditive Approaches to Mixed Integer Programming

Subadditive Approaches to Mixed Integer Programming Subadditive Approaches to Mixed Integer Programming by Babak Moazzez A thesis submitted to the Faculty of Graduate and Postdoctoral Affairs in partial fulfillment of the requirements for the degree of

More information

Tight Formulations for Some Simple Mixed Integer Programs and Convex Objective Integer Programs

Tight Formulations for Some Simple Mixed Integer Programs and Convex Objective Integer Programs Tight Formulations for Some Simple Mixed Integer Programs and Convex Objective Integer Programs Andrew J. Miller 1 Laurence A. Wolsey 2 March 19, 2008 Abstract We study the polyhedral structure of simple

More information

Cut-Generating Functions for Integer Linear Programming

Cut-Generating Functions for Integer Linear Programming Cut-Generating Functions for Integer Linear Programming By: Masumi Sugiyama Faculty advisor: Matthias Köppe Senior thesis June 2015 UNIVERSITY OF CALIFORNIA, DAVIS COLLEGE OF LETTERS AND SCIENCE DEPARTMENT

More information

On Sublinear Inequalities for Mixed Integer Conic Programs

On Sublinear Inequalities for Mixed Integer Conic Programs Noname manuscript No. (will be inserted by the editor) On Sublinear Inequalities for Mixed Integer Conic Programs Fatma Kılınç-Karzan Daniel E. Steffy Submitted: December 2014; Revised: July 2015 Abstract

More information

The Triangle Closure is a Polyhedron

The Triangle Closure is a Polyhedron The Triangle Closure is a Polyhedron Amitabh Basu Robert Hildebrand Matthias Köppe January 8, 23 Abstract Recently, cutting planes derived from maximal lattice-free convex sets have been studied intensively

More information

Lifting properties of maximal lattice-free polyhedra

Lifting properties of maximal lattice-free polyhedra Lifting properties of maximal lattice-free polyhedra Gennadiy Averkov and Amitabh Basu January 16, 2015 Abstract We study the uniqueness of minimal liftings of cut-generating functions obtained from maximal

More information

On Sublinear Inequalities for Mixed Integer Conic Programs

On Sublinear Inequalities for Mixed Integer Conic Programs Noname manuscript No. (will be inserted by the editor) On Sublinear Inequalities for Mixed Integer Conic Programs Fatma Kılınç-Karzan Daniel E. Steffy Submitted: December 2014; Revised: July 7, 2015 Abstract

More information

Unique lifting of integer variables in minimal inequalities

Unique lifting of integer variables in minimal inequalities Unique liting o integer variables in minimal inequalities Amitabh Basu 1, Manoel Campêlo 2,6, Michele Conorti 3,8, Gérard Cornuéjols 4,7, Giacomo Zambelli 5,8 December 6, 2011 Abstract This paper contributes

More information

Split Rank of Triangle and Quadrilateral Inequalities

Split Rank of Triangle and Quadrilateral Inequalities Split Rank of Triangle and Quadrilateral Inequalities Santanu Dey 1 Quentin Louveaux 2 June 4, 2009 Abstract A simple relaxation of two rows of a simplex tableau is a mixed integer set consisting of two

More information

Split Cuts for Convex Nonlinear Mixed Integer Programming

Split Cuts for Convex Nonlinear Mixed Integer Programming Split Cuts for Convex Nonlinear Mixed Integer Programming Juan Pablo Vielma University of Pittsburgh joint work with D. Dadush and S. S. Dey S. Modaresi and M. Kılınç Georgia Institute of Technology University

More information

Maximal S-free convex sets and the Helly number

Maximal S-free convex sets and the Helly number Maximal S-free convex sets and the Helly number Michele Conforti Marco Di Summa Abstract Given a subset S of R d, the Helly number h(s) is the largest size of an inclusionwise minimal family of convex

More information

n-step mingling inequalities: new facets for the mixed-integer knapsack set

n-step mingling inequalities: new facets for the mixed-integer knapsack set Math. Program., Ser. A (2012) 132:79 98 DOI 10.1007/s10107-010-0382-6 FULL LENGTH PAPER n-step mingling inequalities: new facets for the mixed-integer knapsack set Alper Atamtürk Kiavash Kianfar Received:

More information

Lecture 2. Split Inequalities and Gomory Mixed Integer Cuts. Tepper School of Business Carnegie Mellon University, Pittsburgh

Lecture 2. Split Inequalities and Gomory Mixed Integer Cuts. Tepper School of Business Carnegie Mellon University, Pittsburgh Lecture 2 Split Inequalities and Gomory Mixed Integer Cuts Gérard Cornuéjols Tepper School of Business Carnegie Mellon University, Pittsburgh Mixed Integer Cuts Gomory 1963 Consider a single constraint

More information

BCOL RESEARCH REPORT 07.04

BCOL RESEARCH REPORT 07.04 BCOL RESEARCH REPORT 07.04 Industrial Engineering & Operations Research University of California, Berkeley, CA 94720-1777 LIFTING FOR CONIC MIXED-INTEGER PROGRAMMING ALPER ATAMTÜRK AND VISHNU NARAYANAN

More information

Constant factor approximations with families of intersection cuts

Constant factor approximations with families of intersection cuts Constant factor approximations with families of intersection cuts Gennadiy Averkov, Amitabh Basu 2,, and Joseph Paat 2, Institute of Mathematical Optimization, Faculty of Mathematics, University of Magdeburg,

More information

1 Maximal Lattice-free Convex Sets

1 Maximal Lattice-free Convex Sets 47-831: Advanced Integer Programming Lecturer: Amitabh Basu Lecture 3 Date: 03/23/2010 In this lecture, we explore the connections between lattices of R n and convex sets in R n. The structures will prove

More information

Lattice closures of polyhedra

Lattice closures of polyhedra Lattice closures of polyhedra Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Oktay Günlük IBM Research gunluk@us.ibm.com April 10, 2017 Diego A. Morán R. Universidad Adolfo Ibañez diego.moran@uai.cl Abstract

More information

On Counting Lattice Points and Chvátal-Gomory Cutting Planes

On Counting Lattice Points and Chvátal-Gomory Cutting Planes On Counting Lattice Points and Chvátal-Gomory Cutting Planes Andrea Lodi 1, Gilles Pesant 2, and Louis-Martin Rousseau 2 1 DEIS, Università di Bologna - andrea.lodi@unibo.it 2 CIRRELT, École Polytechnique

More information

Change in the State of the Art of (Mixed) Integer Programming

Change in the State of the Art of (Mixed) Integer Programming Change in the State of the Art of (Mixed) Integer Programming 1977 Vancouver Advanced Research Institute 24 papers 16 reports 1 paper computational, 4 small instances Report on computational aspects: only

More information

Lifting properties of maximal lattice-free polyhedra

Lifting properties of maximal lattice-free polyhedra Lifting properties of maximal lattice-free polyhedra Gennadiy Averkov and Amitabh Basu April 29, 2014 Abstract We study the uniqueness of minimal liftings of cut-generating functions obtained from maximal

More information

Computational Experiments with Cross and Crooked Cross Cuts

Computational Experiments with Cross and Crooked Cross Cuts Submitted to INFORMS Journal on Computing manuscript (Please, provide the mansucript number!) Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes

More information

On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs

On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs Yogesh Awate Tepper School of Business, Carnegie Mellon University, Pittsburgh,

More information

Constraint Qualification Failure in Action

Constraint Qualification Failure in Action Constraint Qualification Failure in Action Hassan Hijazi a,, Leo Liberti b a The Australian National University, Data61-CSIRO, Canberra ACT 2601, Australia b CNRS, LIX, Ecole Polytechnique, 91128, Palaiseau,

More information

On Subadditive Duality for Conic Mixed-Integer Programs

On Subadditive Duality for Conic Mixed-Integer Programs arxiv:1808.10419v1 [math.oc] 30 Aug 2018 On Subadditive Duality for Conic Mixed-Integer Programs Diego A. Morán R. Burak Kocuk Abstract It is known that the subadditive dual of a conic mixed-integer program

More information

OPTIMA. Mathematical Programming Society Newsletter. 1 Steve Wright, MPS Chair s Column

OPTIMA. Mathematical Programming Society Newsletter. 1 Steve Wright, MPS Chair s Column OPTIMA Mathematical Programming Society Newsletter 80 Steve Wright MPS Chair s Column September 6, 2009. I m writing in the wake of ISMP 2009 in Chicago, which ended last weekend. All involved in the organization

More information

Computational Integer Programming Universidad de los Andes. Lecture 1. Dr. Ted Ralphs

Computational Integer Programming Universidad de los Andes. Lecture 1. Dr. Ted Ralphs Computational Integer Programming Universidad de los Andes Lecture 1 Dr. Ted Ralphs MIP Lecture 1 1 Quick Introduction Bio Course web site Course structure http://coral.ie.lehigh.edu/ ted/teaching/mip

More information

The strength of multi-row models 1

The strength of multi-row models 1 The strength of multi-row models 1 Quentin Louveaux 2 Laurent Poirrier 3 Domenico Salvagnin 4 October 6, 2014 Abstract We develop a method for computing facet-defining valid inequalities for any mixed-integer

More information

Cutting planes from extended LP formulations

Cutting planes from extended LP formulations Cutting planes from extended LP formulations Merve Bodur University of Wisconsin-Madison mbodur@wisc.edu Sanjeeb Dash IBM Research sanjeebd@us.ibm.com March 7, 2016 Oktay Günlük IBM Research gunluk@us.ibm.com

More information

On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs

On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs On the relative strength of families of intersection cuts arising from pairs of tableau constraints in mixed integer programs Yogesh Awate Tepper School of Business, Carnegie Mellon University, Pittsburgh,

More information

An introduction to some aspects of functional analysis

An introduction to some aspects of functional analysis An introduction to some aspects of functional analysis Stephen Semmes Rice University Abstract These informal notes deal with some very basic objects in functional analysis, including norms and seminorms

More information

Lifting for conic mixed-integer programming

Lifting for conic mixed-integer programming Math. Program., Ser. A DOI 1.17/s117-9-282-9 FULL LENGTH PAPER Lifting for conic mixed-integer programming Alper Atamtürk Vishnu Narayanan Received: 13 March 28 / Accepted: 28 January 29 The Author(s)

More information

A Note on the MIR closure

A Note on the MIR closure A Note on the MIR closure Pierre Bonami Tepper School of Business, Carnegie Mellon University, Pittsburgh PA 53, USA. Gérard Cornuéjols Tepper School of Business, Carnegie Mellon University, Pittsburgh

More information

The Master Equality Polyhedron: Two-Slope Facets and Separation Algorithm

The Master Equality Polyhedron: Two-Slope Facets and Separation Algorithm The Master Equality Polyhedron: Two-Slope Facets and Separation Algorithm by Xiaojing Wang A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master

More information

Integer Programming ISE 418. Lecture 13b. Dr. Ted Ralphs

Integer Programming ISE 418. Lecture 13b. Dr. Ted Ralphs Integer Programming ISE 418 Lecture 13b Dr. Ted Ralphs ISE 418 Lecture 13b 1 Reading for This Lecture Nemhauser and Wolsey Sections II.1.1-II.1.3, II.1.6 Wolsey Chapter 8 CCZ Chapters 5 and 6 Valid Inequalities

More information

A probabilistic comparison of split and type 1 triangle cuts for two row mixed-integer programs

A probabilistic comparison of split and type 1 triangle cuts for two row mixed-integer programs A probabilistic comparison of split and type 1 triangle cuts for two row mixed-integer programs Qie He, Shabbir Ahmed, George L. Nemhauser H. Milton Stewart School of Industrial & Systems Engineering Georgia

More information

Strong Dual for Conic Mixed-Integer Programs

Strong Dual for Conic Mixed-Integer Programs Strong Dual for Conic Mixed-Integer Programs Diego A. Morán R. Santanu S. Dey Juan Pablo Vielma July 14, 011 Abstract Mixed-integer conic programming is a generalization of mixed-integer linear programming.

More information

Lifting 2-integer knapsack inequalities

Lifting 2-integer knapsack inequalities Lifting 2-integer knapsack inequalities A. Agra University of Aveiro and C.I.O. aagra@mat.ua.pt M.F. Constantino D.E.I.O., University of Lisbon and C.I.O. miguel.constantino@fc.ul.pt October 1, 2003 Abstract

More information

On the Rational Polytopes with Chvátal Rank 1

On the Rational Polytopes with Chvátal Rank 1 On the Rational Polytopes with Chvátal Rank 1 Gérard Cornuéjols Dabeen Lee Yanjun Li December 2016, revised May 2018 Abstract We study the following problem: given a rational polytope with Chvátal rank

More information

Mixed-integer nonlinear programming, Conic programming, Duality, Cutting

Mixed-integer nonlinear programming, Conic programming, Duality, Cutting A STRONG DUAL FOR CONIC MIXED-INTEGER PROGRAMS DIEGO A. MORÁN R., SANTANU S. DEY, AND JUAN PABLO VIELMA Abstract. Mixed-integer conic programming is a generalization of mixed-integer linear programming.

More information

The continuous knapsack set

The continuous knapsack set The continuous knapsack set Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Oktay Günlük IBM Research gunluk@us.ibm.com January 31, 2014 Laurence Wolsey Core laurence.wolsey@uclouvain.be Abstract We study

More information

The continuous knapsack set

The continuous knapsack set The continuous knapsack set Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Oktay Günlük IBM Research gunluk@us.ibm.com December 18, 2014 Laurence Wolsey Core laurence.wolsey@uclouvain.be Abstract We study

More information

Convex hull of two quadratic or a conic quadratic and a quadratic inequality

Convex hull of two quadratic or a conic quadratic and a quadratic inequality Noname manuscript No. (will be inserted by the editor) Convex hull of two quadratic or a conic quadratic and a quadratic inequality Sina Modaresi Juan Pablo Vielma the date of receipt and acceptance should

More information

Computational Experiments with Cross and Crooked Cross Cuts

Computational Experiments with Cross and Crooked Cross Cuts Computational Experiments with Cross and Crooked Cross Cuts Sanjeeb Dash IBM Research sanjeebd@us.ibm.com Oktay Günlük IBM Research gunluk@us.ibm.com Juan Pablo Vielma Massachusetts Institute of Technology

More information

Asteroide Santana, Santanu S. Dey. December 4, School of Industrial and Systems Engineering, Georgia Institute of Technology

Asteroide Santana, Santanu S. Dey. December 4, School of Industrial and Systems Engineering, Georgia Institute of Technology for Some for Asteroide Santana, Santanu S. Dey School of Industrial Systems Engineering, Georgia Institute of Technology December 4, 2016 1 / 38 1 1.1 Conic integer programs for Conic integer programs

More information

MEP123: Master Equality Polyhedron with one, two or three rows

MEP123: Master Equality Polyhedron with one, two or three rows 1/17 MEP123: Master Equality Polyhedron with one, two or three rows Oktay Günlük Mathematical Sciences Department IBM Research January, 29 joint work with Sanjeeb Dash and Ricardo Fukasawa 2/17 Master

More information

Lift-and-Project Inequalities

Lift-and-Project Inequalities Lift-and-Project Inequalities Q. Louveaux Abstract The lift-and-project technique is a systematic way to generate valid inequalities for a mixed binary program. The technique is interesting both on the

More information

Two-Term Disjunctions on the Second-Order Cone

Two-Term Disjunctions on the Second-Order Cone Noname manuscript No. (will be inserted by the editor) Two-Term Disjunctions on the Second-Order Cone Fatma Kılınç-Karzan Sercan Yıldız the date of receipt and acceptance should be inserted later Abstract

More information

The traveling salesman problem

The traveling salesman problem Chapter 58 The traveling salesman problem The traveling salesman problem (TSP) asks for a shortest Hamiltonian circuit in a graph. It belongs to the most seductive problems in combinatorial optimization,

More information

Description of 2-integer continuous knapsack polyhedra

Description of 2-integer continuous knapsack polyhedra Discrete Optimization 3 (006) 95 0 www.elsevier.com/locate/disopt Description of -integer continuous knapsack polyhedra A. Agra a,, M. Constantino b a Department of Mathematics and CEOC, University of

More information

THE REAL NUMBERS Chapter #4

THE REAL NUMBERS Chapter #4 FOUNDATIONS OF ANALYSIS FALL 2008 TRUE/FALSE QUESTIONS THE REAL NUMBERS Chapter #4 (1) Every element in a field has a multiplicative inverse. (2) In a field the additive inverse of 1 is 0. (3) In a field

More information

Lecture 7: Semidefinite programming

Lecture 7: Semidefinite programming CS 766/QIC 820 Theory of Quantum Information (Fall 2011) Lecture 7: Semidefinite programming This lecture is on semidefinite programming, which is a powerful technique from both an analytic and computational

More information

Integer Programming Methods LNMB

Integer Programming Methods LNMB Integer Programming Methods LNMB 2017 2018 Dion Gijswijt homepage.tudelft.nl/64a8q/intpm/ Dion Gijswijt Intro IntPM 2017-2018 1 / 24 Organisation Webpage: homepage.tudelft.nl/64a8q/intpm/ Book: Integer

More information