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‘Multidimensional’ extensions and a nested dual approach for the m-median problem
Authors:Pitu B. Mirchandani  Aissa Oudjit  Richard T. Wong
Affiliation:Rensselaer Polytechnic Institute, Troy, NY 12181, U.S.A.;CEN, CDTA-Architectures des Systemes, 2 Bd Frantz Fanon, Alger, Algeria;Purdue University, West Lafayette, IN 47907, U.S.A.
Abstract:A general framework for modeling median type locational decisions, where (i) travel costs and demands may be stochastic, (ii) multiple services or commodities need to be considered, and/or (iii) multiple median type objectives might exist, is presented—using the concept of “multidimensional networks”. The classical m-median problem, the stochastic m-median problem, the multicommodity m-median problem and and multiobjective m-median problem are defined within this framework.By an appropriate transformation of variables, the multidimensional m-median problem simplifies to the classical m-median problem but with a K-fold increase in the number of nodes, where K is the number of dimensions of the network. A nested dual approach to solve the resulting classical m-median problem, that uses Erlenkotter's facility location scheme as a subroutine, is presented. Computational results indicate that the procedure may perhaps be the best available one to solve the m-median problem exactly.
Keywords:Location  general transportation  Lagrange multipliers  networks  integer programming
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