A CONVEX SUBMODEL WITH APPLICATION TO SYSTEM DESIGN

Javier Salmerón () and Ángel Marín ()
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Javier Salmerón: Operations Research Department, Naval Postgraduate School, Monterey, CA, 93943, USA
Ángel Marín: Departamento de Matemática Aplicada y Estadística, E.T.S.I. Aeronáuticos, Universidad Politécnica de Madrid, 28040 Madrid, Spain

Asia-Pacific Journal of Operational Research (APJOR), 2004, vol. 21, issue 01, 9-33

Abstract: In this paper, we present an algorithm to solve a particular convex model explicitly. The model may massively arise when, for example, Benders decomposition or Lagrangean relaxation-decomposition is applied to solve large design problems in facility location and capacity expansion. To attain the optimal solution of the model, we analyze its Karush–Kuhn–Tucker optimality conditions and develop a constructive algorithm that provides the optimal primal and dual solutions. This approach yields better performance than other convex optimization techniques.

Keywords: Convex programming; decomposition methods; Karush–Kuhn–Tucker optimality conditions (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1142/S0217595904000047

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