HubLocator: an exact solution method for the multiple allocation hub location problem
Computers and Operations Research - Location analysis
Heuristic concentration for the p-median: an example demonstrating how and why it works
Computers and Operations Research
Location models for airline hubs behaving as M/D/c queues
Computers and Operations Research
A branch and cut algorithm for hub location problems with single assignment
Mathematical Programming: Series A and B
Adapting polyhedral properties from facility to hub location problems
Discrete Applied Mathematics - The fourth international colloquium on graphs and optimisation (GO-IV)
Formulating and solving splittable capacitated multiple allocation hub location problems
Computers and Operations Research - Articles presented at the conference on routing and location (CORAL)
Solving the hub location problem with modular link capacities
Computers and Operations Research - Articles presented at the conference on routing and location (CORAL)
Hub Arc Location Problems: Part I-Introduction and Results
Management Science
Hub Arc Location Problems: Part II-Formulations and Optimal Algorithms
Management Science
Solving the hub location problem in a star–star network
Networks - Special Issue In Memory of Stefano Pallottino
The heuristic concentration-integer and its application to a class of location problems
Computers and Operations Research
The uncapacitated hub location problem in networks under decentralized management
Computers and Operations Research
Twenty-Five Years of Hub Location Research
Transportation Science
Computers and Industrial Engineering
A Stackelberg hub arc location model for a competitive environment
Computers and Operations Research
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We formulate the competitive hub location problem in which customers have gravity-like utility functions. In the resulting probabilistic model, customers choose an airline depending on a combination of functions of flying time and fare. The (conditional) follower's hub location problem is solved by means of a heuristic concentration method. Computational experience is obtained using the Australian data frequently used in the literature. The results demonstrate that the proposed method is viable even for problems of realistic size, and the results appear quite robust with respect to the leader's hub locations.