On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

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

How do the Risk Equity Techniques Affect on Intercity Road Network Accessibility? An Empirical Study

Due to existing risk on hazardous materials transportation, it is essential to avoid risk agglomeration over the specific edges which are frequently used on the intercity road network. Therefore, local and/or national authorities are dealing with distributing risk over the network while risk distribution may affect on the network accessibility. The aim of this study is to propose a procedure and develop mathematical models to distribute Hazmat transport risk, named risk equity, on the intercity road network and investigate the effects on the network accessibility. Accessibility is defined as dividing transport demand by distance, where the Min (Max) risk distribution technique is utilized for risk equity over the network. The effects have been investigated on a medium size of intercity road network in Guilan province, at the north of Iran. The proposed procedure and mathematical models have been run using experimental data including 46 nodes and 126 two-way edges including Hazmat Origin-Destination matrix. The results revealed that risk distribution technique has significant effects on network accessibility in which nodes’ accessibilities are statistically affected by risk equity models

DESIGN AND DEVELOPMENT OF A SMART ADVISORY SYSTEM FOR HAZARDOUS MATERIALS TRANSPORTATION RISK ANALYSIS VIA QUANTITATIVE APPROACHES

Safe transportation of hazardous materials is critical as it has a high potential of catastrophic accidents depending on the amount of transported product, its hazardous characteristics and the environmental conditions. Consequently, an efficient, smart and reliable intervention is essential to enhance prediction on the impacts of transportation hazards. Although various risk assessment techniques have been used in industry and regulatory bodies, they were developed for evaluating risk of hazardous materials for fixed installation cases instead of moving risk sources. This study applies the Transportation Risk Analysis (TRA), which is an extension of a well-known Quantitative Risk Analysis (QRA) technique in developing and design a Smart Advisory Systems (SAS), to determine the safest routes for transportation of hazardous materials according to Malaysia scenario

Potential Terrorist Uses of Highway-Borne Hazardous Materials, MTI Report 09-03

The Department of Homeland Security (DHS) has requested that the Mineta Transportation Institutes National Transportation Security Center of Excellence (MTI NTSCOE) provide any research it has or insights it can provide on the security risks created by the highway transportation of hazardous materials. This request was submitted to MTI/NSTC as a National Transportation Security Center of Excellence. In response, MTI/NTSC reviewed and revised research performed in 2007 and 2008 and assembled a small team of terrorism and emergency-response experts, led by Center Director Brian Michael Jenkins, to report on the risks of terrorists using highway shipments of flammable liquids (e.g., gasoline tankers) to cause casualties anywhere, and ways to reduce those risks. This report has been provided to DHS. The teams first focus was on surface transportation targets, including highway infrastructure, and also public transportation stations. As a full understanding of these materials, and their use against various targets became revealed, the team shifted with urgency to the far more plentiful targets outside of surface transportation where people gather and can be killed or injured. However, the team is concerned to return to the top of the use of these materials against public transit stations and recommends it as a separate subject for urgent research

A procedure for optimizing hazardous materials transportation including road infrastructures' characteristics and door-to-door attempted deliveries

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Risk based, multi objective vehicle routing problem for hazardous materials: a test case in downstream fuel logistics

Abstract The paper analyses a practical case of study related to the distribution of fuels for the Total Erg Oil Company to the service stations located in the Province of Rome (Italy). The problem is formulated as a capacitated vehicle routing problem with time windows, where several heuristic procedures have been tested, considering both static and dynamic travel times. With respect to the standard operational costs used typically, a multivariable objective function has been proposed which takes into account also a new risk index. The risk index proposed is function of the population density of the zones covered by each path and of the estimated number of road accidents on each road link. In such a way, we take into account the population's exposure to the risk associated with an incidental event involving a fuel tank. The obtained output is the set of planned routes with minimum service cost and minimum risk. Results demonstrate how an accurate planning of the service saves up to 3 hours and 30 km on a daily basis compared to a benchmark. Moreover, the distribution company can parameterize the configuration of the service, by varying the weight adopted in order to include the risk index. Including the risk index may bring to a higher safety route planning, with an increase of the operating costs of only 2%

A Methodology to Develop a Decision Model Using a Large Categorical Database with Application to Identifying Critical Variables during a Transport-Related Hazardous Materials Release

An important problem in the use of large categorical databases is extracting information to make decisions, including identification of critical variables. Due to the complexity of a dataset containing many records, variables, and categories, a methodology for simplification and measurement of associations is needed to build the decision model. To this end, the proposed methodology uses existing methods for categorical exploratory analysis. Specifically, latent class analysis and loglinear modeling, which together constitute a three-step, non-simultaneous approach, were used to simplify the variables and measure their associations, respectively. This methodology has not been used to extract data-driven decision models from large categorical databases. A case in point is a large categorical database at the DoT for hazardous materials releases during transportation. This dataset is important due to the risk from an unintentional release. However, due to the lack of a data-congruent decision model of a hazmat release, current decision making, including critical variable identification, is limited at the Office of Hazardous Materials within the DoT. This gap in modeling of a release is paralleled by a similar gap in the hazmat transportation literature. The literature has an operations research and quantitative risk assessment focus, in which the models consist of simple risk equations or more complex, theoretical equations. Thus, based on critical opportunities at the DoT and gaps in the literature, the proposed methodology was demonstrated using the hazmat release database. The methodology can be applied to other categorical databases for extracting decision models, such as those at the National Center for Health Statistics. A key goal of the decision model, a Bayesian network, was identification of the most influential variables relative to two consequences or measures of risk in a hazmat release, dollar loss and release quantity. The most influential variables for dollar loss were found to be variables related to container failure, specifically the causing object and item-area of failure on the container. Similarly, for release quantity, the container failure variables were also most influential, specifically the contributing action and failure mode. In addition, potential changes in these variables for reducing consequences were identified