Mixed Integer Rounding Inequalities Research Articles

On [formula omitted]-step MIR and partition inequalities for integer knapsack and single-node capacitated flow sets

Pochet and Wolsey [Y. Pochet, L.A. Wolsey, Integer knapsack and flow covers with divisible coefficients: polyhedra, optimization and separation, Discrete Applied Mathematics 59 (1995) 57–74] introduced partition inequalities for three substructures arising in various mixed integer programs, namely the integer knapsack set with nonnegative divisible/arbitrary coefficients and two forms of single-node capacitated flow set with divisible coefficients. They developed the partition inequalities by proving properties of the optimal solution in optimizing a linear function over these sets. More recently, the author and Fathi [K. Kianfar, Y. Fathi, Generalized mixed integer rounding inequalities: facets for infinite group polyhedra, Mathematical Programming 120 (2009) 313–346] have introduced the n-step mixed integer rounding (MIR) inequalities for the mixed-integer knapsack set with arbitrary coefficients through a generalization of MIR. In this paper, we show that the n-step MIR generates facet-defining inequalities not only for the three sets considered by Pochet and Wolsey but also for their generalization to the case where coefficients are not necessarily divisible. In the case of divisible coefficients, n-step MIR directly generates the partition inequalities for all three sets (and in some cases stronger inequalities for one of the sets). We show that n-step MIR gives facets for the integer knapsack set with arbitrary coefficients that either dominate or are not obtainable by the partition inequalities. Also, using the n-step MIR, we introduce families of facets for the two capacitated flow sets with arbitrary coefficients for the first time. Our results provide a new perspective based on n-step MIR into the polyhedral properties of these three substructures, extend them to the case of arbitrary coefficients, and underscore the power of n-step MIR to easily generate strong valid inequalities.

Computational Testing of a Separation Procedure for the Knapsack Set with a Single Continuous Variable

We study an exact separation procedure—SEP-MK—for the knapsack set with a single continuous variable XMK. Then, we address the question of whether SEP-MK can be of practical use in tightening mixed-integer programming (MIP) formulations when using standard (floating-point) MIP solvers. To this purpose, we present a separation procedure for MIP problems—SEP-MIPMK—where we derive knapsack sets of the form XMK by aggregating the continuous variables in the mixed knapsack inequalities of the formulation. Then, we use SEP-MK to generate cutting planes. Before the continuous variables are aggregated, the mixed knapsack inequalities are modified through the use of a bound substitution procedure to take into account fixed and variable bounds on the continuous variables. Bound substitution is made according to some heuristic rules, so even if its basic component SEP-MK is “exact,” the overall separation procedure for MIP problems, SEP-MIPMK, is heuristic. We perform a computational study on a wide set of mixed-integer programming instances from the MIPLIB 2003 [Achterberg, T., T. Koch, A. Martin. 2006. Mixed Integer Problem Library (MIPLIB) 2003. Konrad-Zuse-Zentrum für Informationstechnik Berlin, Berlin. http://miplib.zib.de] and Mittelmann [Mittelmann, H. 2010. MILP testcases. http://plato.asu.edu/ftp/milp] benchmark sets. Computational experiments confirm that lifted cover and mixed-integer rounding (MIR) inequalities are effective from a computational viewpoint. Nevertheless, there are several instances where SEP-MIPMK is able to significantly raise the lower bounds given by lifted cover and MIR inequalities.

Generating facets for finite master cyclic group polyhedra using n-step mixed integer rounding functions

The n-step mixed integer rounding (MIR) functions generate n-step MIR inequalities for MIP problems and are facets for the infinite group problems. We show that the n-step MIR functions also directly generate facets for the finite master cyclic group polyhedra especially in many cases where the breakpoints of the n-step MIR function are not necessarily at the elements of the group (hence the linear interpolation of the facet coefficients obtained has more than two slopes).

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

The n-step mixed integer rounding (MIR) inequalities of Kianfar and Fathi (Math Program 120(2):313–346, 2009) are valid inequalities for the mixed-integer knapsack set that are derived by using periodic n-step MIR functions and define facets for group problems. The mingling and 2-step mingling inequalities of Atamtürk and Günlük (Math Program 123(2):315–338, 2010) are also derived based on MIR and they incorporate upper bounds on the integer variables. It has been shown that these inequalities are facet-defining for the mixed integer knapsack set under certain conditions and generalize several well-known valid inequalities. In this paper, we introduce new classes of valid inequalities for the mixed-integer knapsack set with bounded integer variables, which we call n-step mingling inequalities (for positive integer n). These inequalities incorporate upper bounds on integer variables into n-step MIR and, therefore, unify the concepts of n-step MIR and mingling in a single class of inequalities. Furthermore, we show that for each n, the n-step mingling inequality defines a facet for the mixed integer knapsack set under certain conditions. For n = 2, we extend the results of Atamtürk and Günlük on facet-defining properties of 2-step mingling inequalities. For n ≥ 3, we present new facets for the mixed integer knapsack set. As a special case we also derive conditions under which the n-step MIR inequalities define facets for the mixed integer knapsack set. In addition, we show that n-step mingling can be used to generate new valid inequalities and facets based on covers and packs defined for mixed integer knapsack sets.

Two-Step MIR Inequalities for Mixed Integer Programs

Two-step mixed integer rounding (MIR) inequalities are valid inequalities derived from a facet of a simple mixed integer set with three variables and one constraint. In this paper we investigate how to effectively use these inequalities as cutting planes for general mixed integer problems. We study the separation problem for single-constraint sets and show that it can be solved in polynomial time when the resulting inequality is required to be sufficiently different from the associated MIR inequalities. We discuss computational issues and present numerical results based on a number of data sets.

On the exact separation of mixed integer knapsack cuts

During the last decades, much research has been conducted on deriving classes of valid inequalities for mixed integer knapsack sets, which we call knapsack cuts. Bixby et al. (The sharpest cut: the impact of Manfred Padberg and his work. MPS/SIAM Series on Optimization, pp. 309–326, 2004) empirically observe that, within the context of branch-and-cut algorithms to solve mixed integer programming problems, the most important inequalities are knapsack cuts derived by the mixed integer rounding (MIR) procedure. In this work we analyze this empirical observation by developing an algorithm to separate over the convex hull of a mixed integer knapsack set. The main feature of this algorithm is a specialized subroutine for optimizing over a mixed integer knapsack set which exploits dominance relationships. The exact separation of knapsack cuts allows us to establish natural benchmarks by which to evaluate specific classes of them. Using these benchmarks on MIPLIB 3.0 and MIPLIB 2003 instances we analyze the performance of MIR inequalities. Our computations, which are performed in exact arithmetic, are surprising: In the vast majority of the instances in which knapsack cuts yield bound improvements, MIR cuts alone achieve over 87% of the observed gain.

Mingling: mixed-integer rounding with bounds

Mixed-integer rounding (MIR) is a simple, yet powerful procedure for generating valid inequalities for mixed-integer programs. When used as cutting planes, MIR inequalities are very effective for mixed-integer programming problems with unbounded integer variables. For problems with bounded integer variables, however, cutting planes based on lifting techniques appear to be more effective. This is not surprising as lifting techniques make explicit use of the bounds on variables, whereas the MIR procedure does not. In this paper we describe a simple procedure, which we call mingling, for incorporating variable bound information into MIR. By explicitly using the variable bounds, the mingling procedure leads to strong inequalities for mixed-integer sets with bounded variables. We show that facets of mixed-integer knapsack sets derived earlier by superadditive lifting techniques can be obtained by the mingling procedure. In particular, the mingling inequalities developed in this paper subsume the continuous cover and reverse continuous cover inequalities of Marchand and Wolsey (Math Program 85:15–33, 1999) as well as the continuous integer knapsack cover and pack inequalities of Atamtürk (Math Program 98:145–175, 2003; Ann Oper Res 139:21–38, 2005). In addition, mingling inequalities give a generalization of the two-step MIR inequalities of Dash and Günlük (Math Program 105:29–53, 2006) under some conditions.

Generalized mixed integer rounding inequalities: facets for infinite group polyhedra

We present a generalization of the mixed integer rounding (MIR) approach for generating valid inequalities for (mixed) integer programming (MIP) problems. For any positive integer n, we develop n facets for a certain (n + 1)-dimensional single-constraint polyhedron in a sequential manner. We then show that for any n, the last of these facets (which we call the n-step MIR facet) can be used to generate a family of valid inequalities for the feasible set of a general (mixed) IP constraint, which we refer to as the n-step MIR inequalities. The Gomory Mixed Integer Cut and the 2-step MIR inequality of Dash and gunluk (Math Program 105(1):29–53, 2006) are the first two families corresponding to n = 1,2, respectively. The n-step MIR inequalities are easily produced using periodic functions which we refer to as the n-step MIR functions. None of these functions dominates the other on its whole period. Finally, we prove that the n-step MIR inequalities generate two-slope facets for the infinite group polyhedra, and hence are potentially strong.

Valid inequalities based on simple mixed-integer sets

In this paper we use facets of simple mixed-integer sets with three variables to derive a parametric family of valid inequalities for general mixed-integer sets. We call these inequalities two-step MIR inequalities as they can be derived by applying the simple mixed-integer rounding (MIR) principle of Wolsey (1998) twice. The two-step MIR inequalities define facets of the master cyclic group polyhedron of Gomory (1969). In addition, they dominate the strong fractional cuts of Letchford and Lodi (2002).

Sequence Independent Lifting for Mixed-Integer Programming

We show that superadditive lifting functions lead to sequence independent lifting of inequalities for general mixed-integer programming. As an application, we note that mixed-integer rounding (MIR) may be viewed as sequence independent lifting. Consequently, we obtain facet conditions for MIR inequalities for mixed-integer knapsacks.

Aggregation and Mixed Integer Rounding to Solve MIPs

In this paper, we discuss the use of mixed integer rounding (MIR) inequalities to solve mixed integer programs. MIR inequalities are essentially Gomory mixed integer cuts. However, as we wish to use problem structure, we insist that MIR inequalities be generated from constraints or simple aggregations of constraints of the original problem. This idea is motivated by the observation that several strong valid inequalities based on specific problem structure can be derived as MIR inequalities. Here we present and test a separation routine for such MIR inequalities that includes a heuristic row aggregation procedure to generate a single knapsack plus continuous variables constraint, complementation of variables, and finally the generation of an MIR inequality. Inserted in a branch-and-cut system, the results suggest that such a routine is a useful additional tool for tackling a variety of mixed integer programming problems.

Mixing mixed-integer inequalities

Mixed-integer rounding (MIR) inequalities play a central role in the development of strong cutting planes for mixed-integer programs. In this paper, we investigate how known MIR inequalities can be combined in order to generate new strong valid inequalities.¶Given a mixed-integer region S and a collection of valid “base” mixed-integer inequalities, we develop a procedure for generating new valid inequalities for S. The starting point of our procedure is to consider the MIR inequalities related with the base inequalities. For any subset of these MIR inequalities, we generate two new inequalities by combining or “mixing” them. We show that the new inequalities are strong in the sense that they fully describe the convex hull of a special mixed-integer region associated with the base inequalities.¶We discuss how the mixing procedure can be used to obtain new classes of strong valid inequalities for various mixed-integer programming problems. In particular, we present examples for production planning, capacitated facility location, capacitated network design, and multiple knapsack problems. We also present preliminary computational results using the mixing procedure to tighten the formulation of some difficult integer programs. Finally we study some extensions of this mixing procedure.

A branch-and-cut algorithm for capacitated network design problems

We present a branch-and-cut algorithm to solve capacitated network design problems. Given a capacitated network and point-to-point traffic demands, the objective is to install more capacity on the edges of the network and route traffic simultaneously, so that the overall cost is minimized. We study a mixed-integer programming formulation of the problem and identify some new facet defining inequalities. These inequalities, together with other known combinatorial and mixed-integer rounding inequalities, are used as cutting planes. To choose the branching variable, we use a new rule called “knapsack branching”. We also report on our computational experience using real-life data.