Benders decomposition for the Hazmat Transport Network Design Problem
Pirmin Fontaine and
Stefan Minner
European Journal of Operational Research, 2018, vol. 267, issue 3, 996-1002
Abstract:
We propose a new method for solving the Hazmat Transport Network Design Problem. In this problem, the government wants to reduce the risk of hazardous accidents for the population by restricting the shipment of hazardous goods on roads. When taking that decision, the government has to anticipate the reaction of the carriers who want to minimize the transportation costs by solving a shortest path problem. We use a bilevel formulation that guarantees stable solutions and transform this model into a mixed-integer linear program by applying the Karush–Kuhn–Tucker conditions. This model is solved to optimality with a multi-cut Benders decomposition. Valid inequalities and an acceleration approach for the master problem further reduce both the iteration number and the run time. Moreover, a partial decomposition technique for bilevel problems is introduced. The numerical study shows the computational benefits of the method and run time savings of more than 50% for large instances compared to a cutting plane method from the literature. The method is especially efficient for large number of shipments. Finally, we show that the bilevel model reduces the risk by 35% on average compared to a two-step decision process that does not anticipate the carriers’ reaction.
Keywords: Transportation; Hazmat Transport Network Design; Bilevel programming; Benders decomposition (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221717311761
Full text for ScienceDirect subscribers only
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:eee:ejores:v:267:y:2018:i:3:p:996-1002
DOI: 10.1016/j.ejor.2017.12.042
Access Statistics for this article
European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati
More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().