During the last decade, significant progresses have been made in solving the Protein Threading Problem (PTP). However, all previous approaches to PTP only perform global sequence–structure alignment. This obvious limitation is in clear contrast with the ”world of sequences”, where local sequence-sequence alignments are widely used to find functionally important regions in families of proteins. ...

Günlük and Pochet [O. Günlük , Y. Pochet: Mixing mixed integer inequalities. Mathematical Programming 90(2001) 429-457] proposed a procedure to mix mixed integer rounding (MIR) inequalities. The mixed MIR inequalities define the convex hull of the mixing set {(y, . . . , y, v) ∈ Z × R+ : α1y + v ≥ βi, i = 1, . . . ,m} and can also be used to generate valid inequalities for general as well as se...

Mixed Integer Programming (MIP) solvers are highly parameterized and randomized matheuristic algorithms. How to properly design experiments for algorithm comparison using MIP solvers is an important topic. In this work, we analyze the performance variability of MIP solvers due to random seed settings and parameter configurations. The application domain is the vertical flight planning problem (V...

Unit Commitment is a fundamental problem in power systems engineering, deciding which generating units to switch on, and when to switch them on, in order to efficiently meet anticipated demand. It has traditionally been solved as a Mixed Integer Programming (MIP) problem but upcoming changes to the power system drastically increase the MIP solution time. In this paper, we discuss the benefits t...

We propose a mixed integer programming (MIP) model and iterative algorithms based on topological orders to solve optimization problems with acyclic constraints on a directed graph. The proposed MIP model has a significantly lower number of constraints compared to popular MIP models based on cycle elimination constraints and triangular inequalities. The proposed iterative algorithms use gradient...

‎in this paper‎, ‎some kkt type sufficient global optimality conditions‎ ‎for general mixed integer nonlinear programming problems with‎ ‎equality and inequality constraints (minpp) are established‎. ‎we achieve‎ ‎this by employing a lagrange function for minpp‎. ‎in addition‎, ‎verifiable sufficient global optimality conditions for general mixed‎ ‎integer quadratic programming problems are der...

In this paper we perform computational studies on two types of integer least squares (ILS) problems that arise in wireless communication applications: unconstrained and box-constrained ILS problems. We perform extensive experiments comparing the performance of the discrete ellipsoid-based search (DEBS) method and the branch-and-cut (B&C) mixed integer programming (MIP) solver, and identify the ...

Given a feasible solution to a Mixed Integer Programming (MIP) model, a natural question is whether that solution can be improved using local search techniques. Local search has been applied very successfully in a variety of other combinatorial optimization domains. Unfortunately, local search relies extensively on the notion of a solution neighborhood, and this neighborhood is almost always ta...

In this paper, we address the scheduling problem involving batch processing machines. The presented mixed integer programming formulation first provides an elegant model for the problem under study. Furthermore, it enables solutions to the problem instances beyond the capability of exact methods developed so far. In order to alleviate computational burden, we propose MIP-based approaches which ...

AI and OR approaches have complementary strengths: AI in domain-specific knowledge representation and OR in efficient mathemat:ical computation. Constraint Logic Programming (CLP), which combines these complementary strengths of the AI and OR approach, is introduced as a new tool to formalize a special class of constraint satisfaction problems that include both qualitative and quantitative cons...