Quadratic Binary Programming Models in Computational Biology

Richard John Forrester, Harvey J Greenberg

Abstract


In this paper we formulate four problems in computational molecular biology as 0-1 quadratic programs. These problems are all NP-hard and the current solution methods used in practice consist of heuristics or approximation algorithms tailored to each problem. Using test problems from scientific databases, we address the question, “Can a general-purpose solver obtain good answers in reasonable time?” In addition, we use the latest heuristics as incumbent solutions to address the question, “Can a general-purpose solver confirm optimality or find an improved solution in reasonable time?” Our computational experiments compare four different reformulation methods: three forms of linearization and one form of quadratic convexification.

Keywords


integer programming; quadratic binary programming; computational biology; sequence alignment; protein folding; contact map overlap; rotamer assignment; protein similarity

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Algorithmic Operations Research. ISSN: 1718-3235