A Simultaneous Magnanti-Wong Method to Accelerate Benders Decomposition for the Metropolitan Container Transportation Problem

Andrew Perrykkad (), Andreas T. Ernst () and Mohan Krishnamoorthy ()
Additional contact information
Andrew Perrykkad: School of Mathematics, Monash University, Clayton, Victoria 3800, Australia
Andreas T. Ernst: School of Mathematics, Monash University, Clayton, Victoria 3800, Australia
Mohan Krishnamoorthy: School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Queensland 4072, Australia

Operations Research, 2022, vol. 70, issue 3, 1531-1559

Abstract: In most Australian cities, container ports are located close to the city, with transportation to and from the port facilitated by trucks. Recently, with a view to reducing container-truck induced city congestion and pollution, state and federal governments have begun championing a modal switch to short-haul rail for these transportation tasks. In this paper, we describe a metropolitan container transportation problem arising from this context that seeks to effectively leverage both modes of transport from a least-cost perspective. We propose a mathematical programming formulation and develop a new modified Benders decomposition method for the problem. We show that the simultaneous Magnanti-Wong method finds Pareto-optimal cuts by solving an augmented version of the subproblem that exploits subproblem dual-degeneracy without destroying its underlying structure. Computational results demonstrate the effectiveness of this routine over the performance of commercial solver implementations of the mathematical programming formulation.

Keywords: Transportation; industries: transportation/shipping; programming: integer; algorithms: benders/decomposition (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.2020.2032 (application/pdf)

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:inm:oropre:v:70:y:2022:i:3:p:1531-1559

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().