## A decomposition algorithm for a class of facility location problems |

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### Contents

LOCATION AND GENERALIZED LAGRANGE MULTIPLIER METHODS | 19 |

ALTERATIONS TO THE DECOMPOSITION ALGORITHM | 49 |

A PARAMETRIC LOCATION ALGORITHM | 67 |

2 other sections not shown

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50 Node Example A-optimality adjacent optimal assignment basis inverse basis vectors Bellmore blem chapter closest open facility computational constraint 1.1b convex combination Cornell University corresponding decomposition algorithm determining Doctor of Philosophy dual variables associated extremal problem facility location problems favorable vector feasible solution Figure given gk(X GLM code indicate integer optima integer programming integer solutions investment constraint j=l k=l jth subproblem Lagrange Multiplier Lagrange Multiplier Methods level of investment linear programming location effects Location Formulations matrix method non-negative number of facilities number of feasible number of iterations objective function opti optimal solution p-median code p-median formulation p-median problem parametric algorithm parametric code partition possible private models private problem procedure Ralph Warner reduce the number required node Rojeski and ReVelle satisfy Section 4.3 service facility shown solu solution to 2.11 solving specified Spielburg Table Theorem thesis tion travel distance user-distance