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Graduate Program in Operations Research, Department of Mechanical Engineering, University of Texas, Austin, Texas 78712-1063
A bundle algorithm is presented to solve a multicommodity network model for determining a recoveryplanfor a single carrier with multiple fleets following a hub closure. The algorithm is shown to provide feasible nearoptimal solutions much more quickly than can be obtained using a standard commercial mixedinteger programming code (CPLEX). In this application, a bundle method is used to solve a Lagrangian relaxation of the integer programming formulation. The full algorithm includes heuristic techniques for finding feasible solutions from the solutions to the relaxed problems. Extensive computations were performed using data from Continental Airlines. The results show that the proposed approach provides faster times to optimality in some cases and always obtains feasible, nearoptimal solutions for larger problems much more quickly than can be found using CPLEX. In addition, while a standard commercial code will provide only one solution, this approach provides multiple highquality solutions.
Graduate Program in Operations Research, Department of Mechanical Engineering, University of Texas, Austin, Texas 78712-1063
Department of Management Science and Information Systems, Graduate School of Business, University of Texas, Austin, Texas 78712-1175
ben{at}calebtech.com
jbard{at}mail.utexas.edu
yu{at}uts.cc.utexas.edu
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