Robust optimization for the hazardous materials transportation network design problem

Chunlin Xin (), Letu Qingge, Jiamin Wang and Binhai Zhu
Additional contact information
Chunlin Xin: Beijing University of Chemical Technology
Letu Qingge: Beijing University of Chemical Technology
Jiamin Wang: Long Island University
Binhai Zhu: Montana State University

Journal of Combinatorial Optimization, 2015, vol. 30, issue 2, No 7, 320-334

Abstract: Abstract In this paper, we reconsider the hazardous materials transportation network design problem with uncertain edge risk (HTNDPUR) which is proved as strong NP-hard. The natural ways to handle NP-hard problems are approximation solutions or FPT algorithms. We prove that the HTNDPUR does not admit any approximation, neither any FPT algorithm, unless P = NP. Furthermore, we utilize the minimax regret criterion to model the HTNDPUR as a bi-level integer programming formulation under edge risk uncertainty, where an interval of possible risk values is associated with each arc. We present a robust heuristic approach that always finds a robust and stable hazmat transportation network. At the end, we test our method on a network of Guangdong province in China to illustrate the efficiency of the algorithm. Our experimental results illustrate that the robust interval risk scenario network performs better than the deterministic scenario network.

Keywords: Hazmat transportation network design; Uncertain edge risk; Computational complexity; Robust optimization; Heuristic algorithms (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
http://link.springer.com/10.1007/s10878-014-9751-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcomop:v:30:y:2015:i:2:d:10.1007_s10878-014-9751-z

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10878

DOI: 10.1007/s10878-014-9751-z

Access Statistics for this article

Journal of Combinatorial Optimization is currently edited by Thai, My T.

More articles in Journal of Combinatorial Optimization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().