File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1007/s11067-014-9236-8
- Scopus: eid_2-s2.0-84914710770
- WOS: WOS:000345972100006
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: A distributionally robust joint chance constrained optimization model for the dynamic network design problem under demand uncertainty
Title | A distributionally robust joint chance constrained optimization model for the dynamic network design problem under demand uncertainty |
---|---|
Authors | |
Keywords | Demand uncertainty Distributionally robust joint chance constraints Dynamic network design problem Semidefinite programming Worst-Case Conditional Value-at-Risk |
Issue Date | 2014 |
Publisher | Springer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=1566-113x |
Citation | Networks and Spatial Economics, 2014, v. 14 n. 3-4, p. 409-433 How to Cite? |
Abstract | This paper develops a distributionally robust joint chance constrained optimization model for a dynamic network design problem (NDP) under demand uncertainty. The major contribution of this paper is to propose an approach to approximate a joint chance-constrained Cell Transmission Model (CTM) based System Optimal Dynamic Network Design Problem with only partial distributional information of uncertain demand. The proposed approximation is tighter than two popular benchmark approximations, namely the Bonferroni’s inequality and second-order cone programming (SOCP) approximations. The resultant formulation is a semidefinite program which is computationally efficient. A numerical experiment is conducted to demonstrate that the proposed approximation approach is superior to the other two approximation approaches in terms of solution quality. The proposed approximation approach may provide useful insights and have broader applicability in traffic management and traffic planning problems under uncertainty. |
Persistent Identifier | http://hdl.handle.net/10722/202639 |
ISSN | 2023 Impact Factor: 1.6 2023 SCImago Journal Rankings: 0.595 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sun, H | en_US |
dc.contributor.author | Gao, Z | en_US |
dc.contributor.author | Szeto, WY | en_US |
dc.contributor.author | Long, J | en_US |
dc.contributor.author | Zhao, F | - |
dc.date.accessioned | 2014-09-19T09:14:10Z | - |
dc.date.available | 2014-09-19T09:14:10Z | - |
dc.date.issued | 2014 | en_US |
dc.identifier.citation | Networks and Spatial Economics, 2014, v. 14 n. 3-4, p. 409-433 | en_US |
dc.identifier.issn | 1566-113X | - |
dc.identifier.uri | http://hdl.handle.net/10722/202639 | - |
dc.description.abstract | This paper develops a distributionally robust joint chance constrained optimization model for a dynamic network design problem (NDP) under demand uncertainty. The major contribution of this paper is to propose an approach to approximate a joint chance-constrained Cell Transmission Model (CTM) based System Optimal Dynamic Network Design Problem with only partial distributional information of uncertain demand. The proposed approximation is tighter than two popular benchmark approximations, namely the Bonferroni’s inequality and second-order cone programming (SOCP) approximations. The resultant formulation is a semidefinite program which is computationally efficient. A numerical experiment is conducted to demonstrate that the proposed approximation approach is superior to the other two approximation approaches in terms of solution quality. The proposed approximation approach may provide useful insights and have broader applicability in traffic management and traffic planning problems under uncertainty. | - |
dc.language | eng | en_US |
dc.publisher | Springer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=1566-113x | - |
dc.relation.ispartof | Networks and Spatial Economics | en_US |
dc.rights | The original publication is available at www.springerlink.com | - |
dc.subject | Demand uncertainty | - |
dc.subject | Distributionally robust joint chance constraints | - |
dc.subject | Dynamic network design problem | - |
dc.subject | Semidefinite programming | - |
dc.subject | Worst-Case Conditional Value-at-Risk | - |
dc.title | A distributionally robust joint chance constrained optimization model for the dynamic network design problem under demand uncertainty | en_US |
dc.type | Article | en_US |
dc.identifier.email | Szeto, WY: ceszeto@hku.hk | en_US |
dc.identifier.authority | Szeto, WY=rp01377 | en_US |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1007/s11067-014-9236-8 | - |
dc.identifier.scopus | eid_2-s2.0-84914710770 | - |
dc.identifier.hkuros | 236069 | en_US |
dc.identifier.volume | 14 | - |
dc.identifier.issue | 3-4 | - |
dc.identifier.spage | 409 | - |
dc.identifier.epage | 433 | - |
dc.identifier.isi | WOS:000345972100006 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 1566-113X | - |