Thesis (M.S.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 110-113). Also available on the Internet.

Thesis (M.S.)--University of Missouri-Columbia, 2003. / Typescript. Includes bibliographical references (leaves 110-113). Also available on the Internet.

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Thesis (M.S.)--University of North Carolina Wilmington, 2008. / Title from PDF title page (viewed September 24, 2008) Includes bibliographical references (p. 46-47)

Thesis (M.S.)--Montana State University--Bozeman, 2004. / Typescript. Chairperson, Graduate Committee: Brendan Mumey. Includes bibliographical references (leaves 45-47).

Smith, T.H.C., Prof.

The aim of this dissertation is to present an algorithm for mixed integer programs which when started with a good heuristic solution can find improved solutions and reduce the error estimate as quickly as possible. This is achieved by using two ideas: a fixed order branch-and-bound method with selective expansion of subproblems and the sieve strategy which uses stronger than optimal bounds. The fixed order branch-and-bound method with selective expansion of subproblems is effective in reducing the error estimate quickly whereas the sieve strategy is effective in reducing the error estimate as well as finding improved solutions quickly. Computational experience is reported.

In the paper, we minimize the holding cost of the safety stock held in a supply chain modeled as a general network. By our assumption, the demand is bounded by a concave function. This fact allows us to formulate the problem as a deterministic optimization. We minimize a concave function over a discrete polyhedron. The main goal of the paper is to describe an algorithm to solve the problem without assuming any particular structure of the underlying supply chain. The algorithm is a branch and bound algorithm. / Singapore-MIT Alliance (SMA)

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No description available.