We consider the integer programming version of inverse optimization. Using superadditive duality, we provide a polyhedral description of the set of inversefeasible objectives. We then describe two algorithmic approaches for solving the inverse integer programming problem.

Examples: Shortest Path, Traveling Salesman, and many many more. . . Just in bioinformatics: Alignments, Threading, Clone-Probe Mapping, Probe Selection, De Novo Peptide Sequencing, SideChain Placement, Maximum-weight Connected Subgraph in PPI Networks, Genome Rearrangements, Cluster Editing, Finding Regulatory Modules, Finding Approximate Gene Clusters, Haplotyping, and many more. . . Example....

Behavioral synthesis, which automatically synthesizes an RTL circuit from a sequential program, is one of promising technologies to improve the design productivity. This paper proposes a function call optimization method in behavioral synthesis from large sequential programs with a number of functions. We formulate the optimization problem using integer linear programming. Our experimental resu...

Abstract Mixed-Integer optimization represents a powerful tool for modeling many optimization problems arising from real-world applications. The Feasibility pump is a heuristic for finding feasible solutions to mixed integer linear problems. In this work, we propose a new feasibility pump approach using concave nondifferentiable penalty functions for measuring solution integrality. We present c...

We introduce a concept that generalizes several different notions of a “centerpoint” in the literature. We develop an oracle-based algorithm for convex mixed-integer optimization based on centerpoints. Further, we show that algorithms based on centerpoints are “best possible” in a certain sense. Motivated by this, we establish structural results about this concept and provide efficient algorith...

Algebraic Methods for Integer Programming Introduction by the Guest Editor Karen Aardal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Second Generation Lift-And-Project Algorithms Daniel Bienstock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Short Rational Generating Functions and Their Applications to Integer Programming Kevin Woods and Ruriko Yos...

The Conic Benchmark Library (CBLIB 2014) is a collection of more than a hundred conic optimization instances under a free and open license policy. It is the first extensive benchmark library for the advancing field of conic mixed-integer and continuous optimization, which is already supported by all major commercial solvers and spans a wide range of industrial applications. The library addresse...

In recent years, it has been increasingly recognized that constraint and integer programming have orthogonal and complementary strengths in stating and solving combinatorial optimization applications. In addition, their integration has become an active research topic. The optimization programming language opl was a first attempt at integrating these technologies both at the language and at the ...

In this paper we consider the modeling and control of railway networks. The main aim of the control is to recover from delays in an optimal way by breaking connections and changing the departure of trains (at a cost). To model the controlled railway system we will use a switching max-pluslinear system description. We define the optimal control design problem for the railway network, and we show...