Introduction to ABACUS - A branch-and-cut System

The software system ABACUS is an object-oriented framework for the implementation of branch-and-cut and branch-and-price algorithms. This paper shows the basics of its application to combinatorial and mixed integer optimization problems

ABACUS - A Branch-And-CUt System, Version 2.0, User's Guide and Reference Manual

ABACUS is a C++ framework for the implementation of branch-and-cut algorithms, branch-and-price algorithms, and their combination for linear mixed integer and combinatorial optimization problems. This manual explains the installation, the design, and the usage of the framework. Both the basic steps and advanced features are discussed. The reference manual describes all classes together with all members that are relevant for the user

An alternative method to crossing minimization on hierarchical graphs

A common method for drawing directed graphs is, as a first step, to partition the vertices into a set of $k$ levels and then, as a second step, to permute the verti ces within the levels such that the number of crossings is minimized. We suggest an alternative method for the second step, namely, removing the minimal number of edges such that the resulting graph is $k$-level planar. For the final diagram the removed edges are reinserted into a $k$-level planar drawing. Hence, i nstead of considering the $k$-level crossing minimization problem, we suggest solv ing the $k$-level planarization problem. In this paper we address the case $k=2$. First, we give a motivation for our appro ach. Then, we address the problem of extracting a 2-level planar subgraph of maximum we ight in a given 2-level graph. This problem is NP-hard. Based on a characterizatio n of 2-level planar graphs, we give an integer linear programming formulation for the 2-level planarization problem. Moreover, we define and investigate the polytop e \2LPS(G) associated with the set of all 2-level planar subgraphs of a given 2 -level graph $G$. We will see that this polytope has full dimension and that the i nequalities occuring in the integer linear description are facet-defining for \2L PS(G). The inequalities in the integer linear programming formulation can be separated in polynomial time, hence they can be used efficiently in a branch-and-cut method fo r solving practical instances of the 2-level planarization problem. Furthermore, we derive new inequalities that substantially improve the quality of the obtained solution. We report on extensive computational results

The k-edge connected subgraph problem: Valid inequalities and Branch-and-Cut

International audienceIn this paper we consider the k-edge connected subgraph problem from a polyhedral point of view. We introduce further classes of valid inequalities for the associated polytope, and describe sufficient conditions for these inequalities to be facet defining. We also devise separation routines for these inequalities, and discuss some reduction operations that can be used in a preprocessing phase for the separation. Using these results, we develop a Branch-and-Cut algorithm and present some computational results

An Integer Programming Approach to Fuzzy Symmetry Detection

The problem of exact symmetry detection in general graphs has received much attention recently. In spite of its NP-hardness, two different algorithms have been presented that in general can solve this problem quickly in practice. However, as most graphs do not admit any exact symmetry at all, the much harder problem of fuzzy symmetry detection arises: a minimal number of certain modifications of the graph should be allowed in order to make it symmetric. We present a general approach to this problem: we allow arbitrary edge deletions and edge creations; every single modification can be given an individual weight. We apply integer programming techniques to solve this problem exactly or heuristically and give runtime results for a first implementation

An Exact Algorithm for Robust Network Design

Modern life heavily relies on communication networks that operate efficiently. A crucial issue for the design of communication networks is robustness with respect to traffic fluctuations, since they often lead to congestion and traffic bottlenecks. In this paper, we address an NP-hard single commodity robust network design problem, where the traffic demands change over time. For k different times of the day, we are given for each node the amount of single-commodity flow it wants to send or to receive. The task is to determine the minimum-cost edge capacities such that the flow can be routed integrally through the net at all times. We present an exact branch-and-cut algorithm, based on a decomposition into biconnected network components, a clever primal heuristic for generating feasible solutions from the linear-programming relaxation, and a general cutting-plane separation routine that is based on projection and lifting. By presenting extensive experimental results on realistic instances from the literature, we show that a suitable combination of these algorithmic components can solve most of these instances to optimality. Furthermore, cutting-plane separation considerably improves the algorithmic performance

Sequential matching problem

Kurzfassung in englisch We present sequential matching problem (SMP) as the problem of finding maximal matchings in a sequence of bipartite graphs, with a strategy of making maximum number of common edges in two consecutive matchings. One application of SMP is the problem of assigning workers to jobs in different time shifts with a goal of minimizing total number of unnecessary switches between jobs. We analyze various algorithmic techniques for this NP-complete problem. We also analyze the Mixed Integer Programming (MIP)problem formulation with huge number of variables and their solution by branch and price method, a column generation scheme with branch and bound, of implicit pricing of nonbasic variables to generate new columns. We then discuss special branching rules, pricing problems, implementation issues, and computational results. Finally we analyze a simpler version of SMP with only two bipartite graphs which is still NP-complete, and an algorithm to augment the common edges in the maximum matchings

The Multilayer Capacitated Survivable IP Network Design Problem : valid inequalities and Branch-and-Cut

Telecommunication networks can be seen as the stacking of several layers like, for instance, IP-over-Optical networks. This infrastructure has to be sufficiently survivable to restore the traffic in the event of a failure. Moreover, it should have adequate capacities so that the demands can be routed between the origin-destinations. In this paper we consider the Multilayer Capacitated Survivable IP Network Design problem. We study two variants of this problem with simple and multiple capacities. We give two multicommodity flow formulations for each variant of this problem and describe some valid inequalities. In particular, we characterize valid inequalities obtained using Chvatal-Gomory procedure from the well known Cutset inequalities. We show that some of these inequalities are facet defining. We discuss separation routines for all the valid inequalities. Using these results, we develop a Branch-and-Cut algorithm and a Branch-and-Cut-and-Price algorithm for each variant and present extensive computational results