A Set-Covering Approach with Column Generation for Parsimony Haplotyping

A Set-Covering Approach with Column Generation for Parsimony Haplotyping

We introduce an exact algorithm, based on Integer Linear Programming, for the parsimony haplotyping problem (PHP). The PHP uses molecular data and is aimed at the determination of a smallest set of haplotypes that explain a given set of genotypes. Our approach is based on a Set Covering formulation of the problem, solved by branch and bound with both columnand rowgeneration. Existing ILP method...

A Column Generation Approach for Pure Parsimony Haplotyping

The knowledge of nucleotides chains that compose the double DNA chain of an individual has a relevant role in detecting diseases and studying populations. However, determining experimentally the single nucleotides chains that, paired, form a certain portion of the DNA is expensive and time-consuming. Mathematical programming approaches have been proposed instead, e.g. formulating the Haplotype ...

A Local Branching Approach for the Set Covering Problem

The set covering problem (SCP) is a well-known combinatorial optimization problem. This paper investigates development of a local branching approach for the SCP. This solution strategy is exact in nature, though it is designed to improve the heuristic behavior of the mixed integer programming solver. The algorithm parameters are tuned by design of experiments approach. The proposed method is te...

A column generation approach for the maximal covering location problem

This article presents a column generation algorithm to calculate new improved lower bounds to the solution of maximal covering location problems formulated as a p-median problem. This reformulation leads to instances that are difficult for column generation methods. The traditional column generation method is compared with the new approach, where the reduced cost criterion used at the column se...

On Parsimony Haplotyping