Managing the transportation of hazardous materials with time windows and uncertainties

Tasouji Hassanpour, Saeed (2022) Managing the transportation of hazardous materials with time windows and uncertainties. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Abstract

The dependence of modern life on numerous hazardous products is an undeniable matter. Considering the dangerous nature of these materials, providing versatile means of transportation is critical and essential. The flexibility and applicability of the mode of truck transportation have made it the most favorable method for conveying hazardous materials (hazmats), yet the shipping performance can be largely susceptible to ever-changing traffic and weather conditions. Inspired by the importance as well as lack of joint considerations of uncertainties, random disruptions, and time-relevant issues, this research plans to examine the location-routing decisions in hazmat transportation by applying stochastic and robust programming models to vehicle routing problems with time windows, so to ensure the corresponding efficiency, efficacy, and equity. Providing effective solutions to the hazmat locationrouting problems is of significant importance for both logistics companies and the government. Exact and heuristic algorithms will be explored for timely and accurate solutions. To assess the practicability and validity of the proposed approaches, realworld case studies will be investigated from the optimization perspective, from which we derive managerial insights that enhance decision-making for system stakeholders. In this regard, this thesis contributes to the current literature in the following three ways. First, we develop a scenario-based robust location-routing model for hazmat transportation with joint consideration of time windows, time-dependency, multiple existing paths between nodes, and disruptions. Second, a stochastic location-routing problem of infectious waste during a pandemic is discussed in a 3-tier network. Embedding temporary facilities, uncertainty, and chance-constrained time windows into the model, a brach-and-price algorithm is developed to solve the model to optimality. Finally, the stochastic location-routing problem of the hazardous waste network is addressed using a three-stage decision framework. The critical features involved in this model are stochastic waste release dates, the risk-aversion parameter, and the proposed decision framework of the model. The framework is built upon a costclustering approach, risk-oriented a priori plan, and recourse actions respectively for location-allocation, routing, and adaption decisions. We summarize the contributions of this thesis, discuss the overall results obtained, and present the potential future research directions.

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