Oğuz, M, Bektaş, T, Bennell, JA orcid.org/0000-0002-5338-2247 et al. (1 more author) (2016) A modelling framework for solving restricted planar location problems using phi-objects. Journal of the Operational Research Society, 67 (8). pp. 1080-1096. ISSN 0160-5682
Abstract
This paper presents a general modelling framework for restricted facility location problems with arbitrarily shaped forbidden regions or barriers, where regions are modelled using phi-objects. Phi-objects are an efficient tool in mathematical modelling of 2D and 3D geometric optimization problems, and are widely used in cutting and packing problems and covering problems. The paper shows that the proposed modelling framework can be applied to both median and centre facility location problems, either with barriers or forbidden regions. The resulting models are either mixed-integer linear or non-linear programming formulations, depending on the shape of the restricted region and the considered distance measure. Using the new framework, all instances from the existing literature for this class of problems are solved to optimality. The paper also introduces and optimally solves a realistic multi-facility problem instance derived from an archipelago vulnerable to earthquakes. This problem instance is significantly more complex than any other instance described in the literature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 Operational Research Society Ltd. This is an author produced version of a paper published in Journal of the Operational Research Society. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | mathematical modelling, facility location, phi-objects |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Faculty Office (LUBS) (Leeds) > Deans Office and Facilities (LUBS) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Nov 2018 13:04 |
Last Modified: | 06 Dec 2018 02:31 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1057/jors.2016.5 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139293 |