Decomposition of loosely coupled integer programs: a multiobjective perspective.

INTEGER programming; INTEGERS; PROBLEM solving

We consider integer programming (IP) problems consisting of (possibly a large number of) subsystems and a small number of coupling constraints that link variables from different subsystems. Such problems are called loosely coupled or nearly decomposable. In this paper, we exploit the idea of resource-directive decomposition to reformulate the problem so that it can be decomposed into a resource-directive master problem and a set of multiobjective programming subproblems. Recent methods developed for solving multiobjective problems enable us to formulate a relaxation of the master problem that is an IP whose solution yields a dual bound on the value of the original IP. This perspective provides a new, general framework for IP decomposition, in which many alternative algorithm designs are possible. Here, we develop one such algorithm, and demonstrate its viability and potential benefits with the aid of computational experiments knapsack-based instances with up to five coupling constraints and 7500 variables, comparing it with both a standard IP solver and a generic branch-and-price solver. [ABSTRACT FROM AUTHOR]

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