We show that every polytope $P\subseteq[0,1]^n$, and more generally every compact convex set, has Chv\’atal rank at most $12.22n^2+n\log_2 n+2n+4$. This improves the $O(n^2\log n)$ bound of Eisenbrand and Schulz and, together with the $\Omega(n^2)$ lower bound of Rothvo{\ss} and Sanit\`a, shows that the maximum Chv\’atal rank of a polytope in $[0,1]^n$ is $\Theta(n^2)$. More … Read more
We revisit the framework of generalized Benders decomposition over a compact but non-finite master domain. We show by counterexample that strong general dual functions alone may fail to guarantee convergence. We then define a condition of uniform local strongness and prove that strong general dual functions satisfying this condition guarantee finite \(\epsilon\)-termination. Finally, we show … Read more
State-of-the-art exact methods for the Maximum Cut problem are based on solving linear and semidefinite programming relaxations embedded into a branch-and-bound algorithm. For linear programming formulations, it was shown recently that it is thereby sufficient to enforce the integrality of the variables associated with the edges of a spanning tree. Our first contribution is to … Read more
Extending a classic result of Giannessi and Tomasin [\textit{Lecture Notes in Comput. Sci. 3}, Springer, 1973, pp. 437–449], this paper shows that a binary-constrained quadratic-defined optimization problem can be formulated as a binary-constrained linear program with linear complementarity constraints (Bi-LPCC). The term “quadratic-defined problems” encompasses many problems that are defined by quadratic functions in the … Read more
We give an exact algorithm for minimizing an arbitrary rational quadratic polynomial xTQx+ cTx+ γ over the integer points of a bounded rational polyhedron Ax ≤b. For n variables and m inequalities, the running time is 2O(n log(n+1))(m+ 1)O(n)φ_{A,Q}^O(n)(1 + φ)O(1), where φ_{A,Q} is one plus the maximum binary encoding length of an entry of … Read more
We consider the exact minimization of a rational cubic polynomial over the integer points of a rational polytope in fixed dimension. Del Pia, Hildebrand, Weismantel, and Zemmer proved polynomial-time solvability in dimension two, while quartic polynomial minimization is already NP-hard in dimension two. We show that the bounded cubic result extends to every fixed dimension. … Read more
A wide range of sparse integer programs admit a block structure in which subproblems interact through a small set of shared variables. Dualizing the linking equalities yields a decomposable Lagrangian relaxation, but generally introduces a duality gap. Recent work shows that this gap can be closed while preserving decomposability by dualizing exponentially large families of … Read more
We give a deterministic polynomial-time algorithm for integer quadratic programming in every fixed dimension: it minimizes an arbitrary rational quadratic exactly over the integer points of a rational polyhedron, or certifies infeasibility or integer unboundedness. The core is a sign test that decides whether \(d^{\mathsf{T}}Qd\ge 0\) for every integer point \(d\) of a bounded symmetric … Read more
Facility location decisions are typically made before demand is fully known, yet most applied studies solve a single deterministic model using expected or nominal demand. This paper formulates and solves a capacitated facility location problem using a real academic benchmark instance, then extends it to a two-stage stochastic program in which facility-opening decisions are made … Read more
When linearizing binary quadratic programs, the most usual way is to replace bilinear products with additional variables constrained to take on consistent values in any feasible solution. In this setting, column generation is a principally desirable solution technique, for instance because the number of such additional linearization variables may be large while many of them … Read more