Link-based multi-class hazmat routing-scheduling problem : a multiple demon approach

Szeto, W. Y., Zanjirani Farahani, Reza and Sumalee, Agachai (2017) Link-based multi-class hazmat routing-scheduling problem : a multiple demon approach. European Journal of Operational Research, ISSN (print) 0377-2217 (Epub Ahead of Print)

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Abstract

This paper addresses a hazmat routing and scheduling problem for a general transportation network with multiple hazmat classes when incident probabilities are unknown or inaccurate. A multi-demon formulation is proposed for this purpose. This formulation is link-based (i.e., the decision variables are link flows) and can be transformed into other forms so that a wide range of solution methods can be used to obtain solutions. This paper also proposes a solution strategy to obtain route flow solutions without relying on exhaustive route enumeration and route generation heuristics. Examples are set up to illustrate the problem properties, the method of obtaining route flows from link flows, and the computational efficiency of the solution strategy. Moreover, a case study is used to illustrate our methodology for real-life hazmat shipment problems. From this case study, we obtain four key insights. First, to have the safest shipment of one type of hazmat, different trucks carrying the same type of hazmat need to take different routes and links. Second, in case of multiple-hazmat transportation, it is recommended to use different routes and links for the shipment of different hazmat types. This may increase travel time but can result in safer shipment. Third, if the degree of connectivity in a transportation network is high, the shipment company may have multiple solutions. Fourth, the hazmat flows on critical links (whose removal would make the network disconnected) must be distributed or scheduled over different periods to have safer shipment.

Item Type: Article
Additional Information: The research was jointly supported by a grant (201311159123) from the University Research Committee of the University of Hong Kong and a grant from National Natural Science Foundation of China, China (71271183).
Research Area: Applied mathematics
Civil engineering
Statistics and operational research
Town and country planning
Faculty, School or Research Centre: Faculty of Business and Law > Kingston Business School (Department of Management) (from August 2013)
Depositing User: Reza Zanjirani Farahani
Date Deposited: 02 Feb 2017 12:03
Last Modified: 23 Feb 2017 10:42
URI: http://eprints.kingston.ac.uk/id/eprint/37446

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