Browsing by Author "Campbell, J. F."

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Open Access
Perspectives on modeling hub location problems
(Elsevier, 2020-10-02) Alumur, S. A.; Campbell, J. F.; Contreras, I.; Yetiş Kara, Bahar; Marianov, V.; O’Kelly, M. E.
The aim of this paper is to provide insights for better modeling hub location problems to help create a road map for future hub location research. We first present a taxonomy to provide a framework for the broad array of hub location models, and then seek to identify key gaps in the literature that provide opportunities for better models. We provide some new perspectives in several areas, including the historical evolution of hub location research, models for economies of scale, and relevant characteristics of different applications. We also provide a succinct summary of state-of-the-art formulation and solution approaches. We conclude with a set of themes that can be addressed in the future for better modeling hub location problems.
Open Access
Spatial analysis of single allocation hub location problems
(Springer, 2016) Peker, M.; Kara, B. Y.; Campbell, J. F.; Alumur, S. A.
Hubs are special facilities that serve as switching, transshipment and sorting nodes in many-to-many distribution systems. Flow is consolidated at hubs to exploit economies of scale and to reduce transportation costs between hubs. In this article, we first identify general features of optimal hub locations for single allocation hub location problems based on only the fundamental problem data (demand for travel and spatial locations). We then exploit this knowledge to develop a straightforward heuristic methodology based on spatial proximity of nodes, dispersion and measures of node importance to delineate subsets of nodes likely to contain optimal hubs. We then develop constraints for these subsets for use in mathematical programming formulations to solve hub location problems. Our methodology can also help narrow an organization’s focus to concentrate on more detailed and qualitative analyses of promising potential hub locations. Results document the value of including both demand magnitude and centrality in measuring node importance and the relevant tradeoffs in solution quality and time.
Open Access
The stratified p-hub center and p-hub maximal covering problems
(Elsevier Ltd, 2022-02-01) Yetiş Kara, Bahar; Ghaffarinasab, N.; Campbell, J. F.
Hub networks are the foundation of many transportation and distribution systems, and real-world hub networks often transport freight or passengers of different service classes. This paper introduces the stratified multiple allocation p-hub center and p-hub maximal covering problems where the traffic corresponding to each origin–destination (O/D) pair is divided into different strata each having a specific service level requirement. The problems are formulated as mixed-integer linear programming (MILP) models and efficient Benders decomposition algorithms are developed for solving large instances. Extensive computational experiments are conducted to demonstrate the efficiency of the proposed mathematical models and the solution algorithms. MILP formulations are also proposed for the generalized versions of the problems that include fixed set-up costs for hubs and hub arcs. Results indicate that the optimal sets of hub locations and hub arcs when considering different strata can be quite dissimilar to those of the traditional p-hub center or p-hub maximal covering problem, but are similar to those of hierarchical hub location problems. Furthermore, models are provided and solved for multi-modal stratified hub location problems with fixed setup costs for hubs and hub arcs. Optimal results show a wide range of network topologies that can be generated, as compared to the classical versions.