A scenario-based hazardous material network design problem with emergency response and toll policy

In the process of shipping hazmats on a road network from origins to destinations, two stakeholders are involved: The authorities who are concerned about the risk of incidents, and the carriers who are concerned about shipping costs. We propose a bilevel model in order to account for the conflicting interests of the two parties. The upper-level (authorities) use different policies: Proactive policies including roadclosure, road-construction and toll policies, and Reactive policies including locating hazmat response teams. Furthermore, scenario-based uncertainty is considered to reflect the variations in demand and shipments. Due to the complexity of the bilevel model, we develop two methods to solve the problem. First, using dual variables and constraints, we reformulate our bilevel model into a single-level model. This method gives us exact optimal solutions. Second, a two-stage heuristic algorithm gives us solutions which are close to the optimal solutions. Then, based on a transportation network in China, experimental results and several sensitivity analyses are presented

OPTIMIZATION OF RAILWAY TRANSPORTATION HAZMATS AND REGULAR COMMODITIES

Transportation of dangerous goods has been receiving more attention in the realm of academic and scientific research during the last few decades as countries have been increasingly becoming industrialized throughout the world, thereby making Hazmats an integral part of our life style. However, the number of scholarly articles in this field is not as many as those of other areas in SCM. Considering the low-probability-and-high-consequence (LPHC) essence of transportation of Hazmats, on the one hand, and immense volume of shipments accounting for more than hundred tons in North America and Europe, on the other, we can safely state that the number of scholarly articles and dissertations have not been proportional to the significance of the subject of interest. On this ground, we conducted our research to contribute towards further developing the domain of Hazmats transportation, and sustainable supply chain management (SSCM), in general terms. Transportation of Hazmats, from logistical standpoint, may include all modes of transport via air, marine, road and rail, as well as intermodal transportation systems. Although road shipment is predominant in most of the literature, railway transportation of Hazmats has proven to be a potentially significant means of transporting dangerous goods with respect to both economies of scale and risk of transportation; these factors, have not just given rise to more thoroughly investigation of intermodal transportation of Hazmats using road and rail networks, but has encouraged the competition between rail and road companies which may indeed have some inherent advantages compared to the other medium due to their infrastructural and technological backgrounds. Truck shipment has ostensibly proven to be providing more flexibility; trains, per contra, provide more reliability in terms of transport risk for conveying Hazmats in bulks. In this thesis, in consonance with the aforementioned motivation, we provide an introduction into the hazardous commodities shipment through rail network in the first chapter of the thesis. Providing relevant statistics on the volume of Hazmat goods, number of accidents, rate of incidents, and rate of fatalities and injuries due to the incidents involving Hazmats, will shed light onto the significance of the topic under study. As well, we review the most pertinent articles while putting more emphasis on the state-of-the-art papers, in chapter two. Following the discussion in chapter 3 and looking at the problem from carrier company’s perspective, a mixed integer quadratically constraint problem (MIQCP) is developed which seeks for the minimization of transportation cost under a set of constraints including those associating with Hazmats. Due to the complexity of the problem, the risk function has been piecewise linearized using a set of auxiliary variables, thereby resulting in an MIP problem. Further, considering the interests of both carrier companies and regulatory agencies, which are minimization of cost and risk, respectively, a multiobjective MINLP model is developed, which has been reduced to an MILP through piecewise linearization of the risk term in the objective function. For both single-objective and multiobjective formulations, model variants with bifurcated and nonbifurcated flows have been presented. Then, in chapter 4, we carry out experiments considering two main cases where the first case presents smaller instances of the problem and the second case focuses on a larger instance of the problem. Eventually, in chapter five, we conclude the dissertation with a summary of the overall discussion as well as presenting some comments on avenues of future work

Emergency response network design for hazardous materials transportation with uncertain demand

Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats), such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method

Pessimistic Hazmat Network Design Problem with Emergency Team Location Considering Uncertain Response Time

Focusing on a road network where hazmat shipments need to be transported from the origins to destinations, this thesis proposes a pessimistic approach to mitigate the risk associated with the transportation of hazardous materials (hazmat). More specifically, two stakeholders are involved in the process, the government entity implementing risk mitigation mechanisms to minimize the maximum network risk, and the hazmat carriers fulfilling hazmat demand to minimize their total travel distance. Due to the conflicting interests and decision process of the two parties, a bilevel model structure is used, and the pessimistic perspective is assumed to ensure that the carriers' worst behavior can be avoided. The risk mitigation mechanisms implemented in this work include 1) network design, where certain road segments (i.e., links/arcs) are made unavailable to hazmat shipments, and 2) locating emergency response teams to attend to possible incidents in a timely manner. The uncertain nature of the response time is incorporated through the chance constraints for both the most and least desired response times, reflecting the satisfaction levels of emergency services. Because of the complexity of the bilevel model, we investigate two solution methods. The first one is to reformulate the problem into a single level model that is linearized later. The second one is a heuristic algorithm that breaks the problem into two stages that can be solved sequentially. We then present experimental results based on a transportation network in China, showing the efficacy of the model in a real-life scenario and providing insights regarding the nature of the solutions

A concise guide to existing and emerging vehicle routing problem variants

Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges

Statistical Investigation of Road and Railway Hazardous Materials Transportation Safety

Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects of different factors on occurrence and consequences of hazmat-related incidents, towards identifying effective policies and countermeasures for improving safety and; 2) quantifying components of risk of hazmat transportation for costs prediction, planning purposes, or short-term decision-making. A comprehensive review of literature, study framework, and available data led to identification of six foci for this dissertation: 1) estimation of hazmat release statistical models for railroad incidents; 2) estimation of rollover and hazmat release statistical models for Cargo Tank Truck (CTT) crashes; 3) analyzing hazmat-involved crashes at highway-rail grade crossings (HRGCs); 4) model-based and non-model-based methods for classifying hazmat release from trains and CTTs; 5) estimation of macroscopic-level statistical models for frequency and severity of rail-based crude oil release incidents; and 6) estimation of statistical models for types and consequences of rail-based crude oil release incidents. Some of the findings of this research include: train derailments increased hazmat release probability more than other incident types; non-collision CTT crashes were more likely to result in rollovers, while rolling over increased the likelihood of hazmat release; at HRGCs, flashing signal lights were associated with lower hazmat release probability from trucks; increase in volume and distance of crude oil shipped from one state to another led to greater frequency and severity of incidents between the two states; and in rail-based crude oil release incidents, non-accident releases were associated with higher probability of gas dispersion, and lower probability of fire and explosion. Based on the results, recommendations regarding policies and countermeasures for improving safety are provided. Advisor: Aemal Khatta

Solving the time capacitated arc routing problem under fuzzy and stochastic travel and service times

Stochastic, as well as fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper we propose a fuzzy simheuristic to solve the Time Capacitated Arc Routing Problem (TCARP) when the nature of the travel time can either be deterministic, stochastic or fuzzy. The main goal is to find a solution (vehicle routes) that minimizes the total time spent in servicing the required arcs. However, due to uncertainty, other characteristics of the solution are also considered. In particular, we illustrate how reliability concepts can enrich the probabilistic information given to decision-makers. In order to solve the aforementioned optimization problem, we extend the concept of simheuristic framework so it can also include fuzzy elements. Hence, both stochastic and fuzzy uncertainty are simultaneously incorporated into the CARP. In order to test our approach, classical CARP instances have been adapted and extended so that customers' demands become either stochastic or fuzzy. The experimental results show the effectiveness of the proposed approach when compared with more traditional ones. In particular, our fuzzy simheuristic is capable of generating new best-known solutions for the stochastic versions of some instances belonging to the tegl, tcarp, val, and rural benchmarks.This work has been partially supported by the Spanish Ministry of Science (PID2019-111100RB-C21/AEI/10.13039/01100011033), as well as by the Barcelona Council and the “laCaixa” Foundation under the framework of the Barcelona Science Plan 2020-2023 (grant21S09355-01) and Generalitat Valenciana (PROMETEO/2021/065).Peer ReviewedPostprint (published version