Mahdavinia, Reihaneh (2025) Optimizing facility locations and network design in hazardous material transportation. Masters thesis, Memorial University of Newfoundland.
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[English]
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Abstract
Optimizing the combined facility location and network design decisions in hazardous material (hazmat) transportation is a complicated problem. The problem involves two stakeholders, the government, whose objective is to minimize the total risk of population exposure to dangerous materials by closing certain roads and nodes, and the carrier, which aims to minimize the total transportation cost by choosing the shortest paths from hazmat generation nodes to processing facilities in addition to reducing hazmat processing and facility construction cost. The government's decisions regarding which roads to close and which nodes to ban impact the carrier's choice of paths and facility location respectively. Hence, the government must anticipate the carrier's reactions while making network (closure or banning) decisions. To address this problem, we propose a novel bi-level programming formulation that integrates both parties' objectives. A cutting plane algorithm is designated to address the bi-level structure for both stakeholders' decisions. Finally, a real-world case study of a transportation network is conducted to demonstrate the effectiveness of our proposed approach in reducing the total risk and cost and reveal insights that can be used to facilitate policy-making in terms of hazmat transportation and processing.
Item Type: | Thesis (Masters) |
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URI: | http://research.library.mun.ca/id/eprint/16867 |
Item ID: | 16867 |
Additional Information: | Includes bibliographical references (pages 51-55) |
Keywords: | hazmat transportation, network design, facility location, cutting-plane algorithm |
Department(s): | Business Administration, Faculty of |
Date: | January 2025 |
Date Type: | Submission |
Digital Object Identifier (DOI): | https://doi.org/10.48336/drb6-8m90 |
Library of Congress Subject Heading: | Hazardous substances--Transportation; Mathematical optimization; Hazardous substances--Government policy; Supply chain management |
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