Hazardous Materials are potentially harmful to people and environment due to their toxic ingredients. Although a significant portion of dangerous goods transportation is via railroads, prevailing studies on dangerous goods transport focus on highway shipments. We present an analytical framework that incorporates the differentiating features of trains in the assessment of risk. Each railcar is a potential source of release, and hence risk assessment of trains requires representation of multiple release sources in the model. We report on the use of the proposed approach for the risk assessment of the Ultra-train that passes through the city of Montreal everyday. The risk assessment methodology is then used to model the operations of freight trains in a network, wherein freight involves both hazardous and regular cargo. We present an optimization model distinct from the conventional ones, a Memetic Algorithm based solution technique, and a number of scenarios intended to gain numerical and managerial insights into the problem. In an effort to combine the economies of trains and efficiencies of trucks, we deal with rail-truck intermodalism for hazardous and non-hazardous cargo. Two special cases and a general case of rail-truck intermodal transportation models, driven by the element of ' time', are presented.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.85961 |
| Date | January 2005 |
| Creators | Verma, Manish |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Doctor of Philosophy (Faculty of Management.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002267659, proquestno: AAINR21707, Theses scanned by UMI/ProQuest. |
Page generated in 0.002 seconds