Let Y be a convex set inRk defined by polynomial inequalities and equations of degree at most d ≥ 2 with integer coefficients of binary length at most l. We show that if the set of optimal solutions of the integer programming problem min{yk | y = (y1, . . . , yk) ∈ Y ∩Zk} is not empty, then the problem has an optimal solution y∗ ∈ Y ∩Zk of binary length ld O(k ). For fixed k, our bound implies ...

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....

Beam search is a tree search procedure where, at each level of the tree, at most w nodes are kept. This results in a metaheuristic whose solving time is polynomial in w. Popular for single-objective problems, beam search has only received little attention in the context of multi-objective optimization. By introducing the concepts of oracle and filter, we define a paradigm to understand multi-ob...

In this article, we provide an overview of the current state of the art with respect to solution of mixed integer linear optimization problems (MILPS) in parallel. Sequential algorithms for solving MILPs have improved substantially in the last two decades and commercial MILP solvers are now considered effective off-the-shelf tools for optimization. Although concerted development of parallel MIL...

Two novel deterministic global optimization algorithms for nonconvex mixed-integer problems (MINLPs) are proposed, using the advances of the BB algorithm for noncon-vex NLPs Adjiman et al. (1998a). The Special Structure Mixed-Integer BB algorithm (SMIN-BB addresses problems with nonconvexities in the continuous variables and linear and mixed-bilinear participation of the binary variables. The G...

We aim to design classifiers that have the interpretability of association rules yet have predictive power on par with the top machine learning algorithms for classification. We propose a novel mixed integer optimization (MIO) approach called Ordered Rules for Classification (ORC) for this task. Our method has two parts. The first part mines a particular frontier of solutions in the space of ru...