Spatial analysis of single allocation hub location problems
dc.citation.epage | 1101 | en_US |
dc.citation.issueNumber | 4 | en_US |
dc.citation.spage | 1075 | en_US |
dc.citation.volumeNumber | 16 | en_US |
dc.contributor.author | Peker, M. | en_US |
dc.contributor.author | Kara, B. Y. | en_US |
dc.contributor.author | Campbell, J. F. | en_US |
dc.contributor.author | Alumur, S. A. | en_US |
dc.date.accessioned | 2018-04-12T10:57:00Z | |
dc.date.available | 2018-04-12T10:57:00Z | en_US |
dc.date.issued | 2016 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | 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. | en_US |
dc.description.provenance | Made available in DSpace on 2018-04-12T10:57:00Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2016 | en |
dc.identifier.doi | 10.1007/s11067-015-9311-9 | en_US |
dc.identifier.eissn | 1572-9427 | |
dc.identifier.issn | 1566-113X | |
dc.identifier.uri | http://hdl.handle.net/11693/36903 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Springer | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1007/s11067-015-9311-9 | en_US |
dc.source.title | Networks and Spatial Economics | en_US |
dc.subject | Clustering nodes | en_US |
dc.subject | Hub location problem | en_US |
dc.subject | Single allocation | en_US |
dc.subject | Spatial distribution | en_US |
dc.subject | Economics | en_US |
dc.subject | Heuristic methods | en_US |
dc.subject | Location | en_US |
dc.subject | Mathematical programming | en_US |
dc.subject | Optimization | en_US |
dc.subject | Site selection | en_US |
dc.subject | Spatial distribution | en_US |
dc.subject | Clustering nodes | en_US |
dc.subject | Economies of scale | en_US |
dc.subject | Hub location problems | en_US |
dc.subject | Many-to-many distribution systems | en_US |
dc.subject | Qualitative analysis | en_US |
dc.subject | Single allocation | en_US |
dc.subject | Spatial proximity | en_US |
dc.subject | Transportation cost | en_US |
dc.subject | Problem solving | en_US |
dc.title | Spatial analysis of single allocation hub location problems | en_US |
dc.type | Article | en_US |
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