Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/104531
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | en_US |
| dc.creator | Zhang, X | en_US |
| dc.creator | Adamatzky, A | en_US |
| dc.creator | Chan, FTS | en_US |
| dc.creator | Mahadevan, S | en_US |
| dc.creator | Deng, Y | en_US |
| dc.date.accessioned | 2024-02-05T08:50:51Z | - |
| dc.date.available | 2024-02-05T08:50:51Z | - |
| dc.identifier.issn | 0254-5330 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/104531 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Springer New York LLC | en_US |
| dc.rights | © Springer Science+Business Media New York 2017 | en_US |
| dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10479-017-2410-x. | en_US |
| dc.subject | Decision making | en_US |
| dc.subject | Network design | en_US |
| dc.subject | Physarum | en_US |
| dc.subject | Supply chain | en_US |
| dc.subject | Sustainability | en_US |
| dc.title | Physarum solver : a bio-inspired method for sustainable supply chain network design problem | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.description.otherinformation | Title on author’s file: Physarum solver: A biologically inspired method for multi-criteria sustainable supply chain network design | en_US |
| dc.identifier.spage | 533 | en_US |
| dc.identifier.epage | 552 | en_US |
| dc.identifier.volume | 254 | en_US |
| dc.identifier.issue | 1-2 | en_US |
| dc.identifier.doi | 10.1007/s10479-017-2410-x | en_US |
| dcterms.abstract | A supplier of products and services aims to minimize the capacity investment cost and the operational cost incurred by unwanted byproducts, e.g. carbon dioxide emission. In this paper, we consider a sustainable supply chain network design problem, where the capacity and the product flow along each link are design variables. We formulate it as a multi-criteria optimization problem. A bio-inspired algorithm is developed to tackle this problem. We illustrate how to design a sustainable supply chain network in three steps. First, we develop a generalized model inspired by the foraging behaviour of slime mould Physarum polycephalum to handle the network optimization with multiple sinks. Second, we propose a strategy to update the link cost iteratively, thus making the Physarum model to converge to a user equilibrium. Third, we perform an equivalent operation to transform a system optimum problem into a corresponding user equilibrium problem so that it is solvable in the Physarum model. The efficiency of the proposed algorithm is illustrated with numerical examples. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Annals of operations research, July 2017, v. 254, no. 1-2, p. 533-552 | en_US |
| dcterms.isPartOf | Annals of operations research | en_US |
| dcterms.issued | 2017-07 | - |
| dc.identifier.scopus | 2-s2.0-85011886781 | - |
| dc.identifier.eissn | 1572-9338 | en_US |
| dc.description.validate | 202402 bcch | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | ISE-0799 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | National Natural Science Foundation of China; National High Technology Research and Development Program of China; Doctor Funding of Southwest University | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 6721080 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Zhang_Physarum_Solver_Bio-inspired.pdf | Pre-Published version | 1.41 MB | Adobe PDF | View/Open |
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