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

A Study on Routing and Scheduling of Hazardous Materials in Railway Transportation

Railway transportation of hazardous materials including Toxic Inhalation Hazard, is crucial to North American economy. Although railway companies have favorable safety records in moving hazardous materials shipments, the possibility of spectacular events resulting from multicars incidents, however low, does exist, and the consequence can be potentially catastrophic in multiple fatalities. The rail disaster in Lac-Mégantic, Quebec, resulted in 47 fatalities and around $1.5 billion damages in 2013, is an example of low-probability high-consequence event. In this dissertation we aim at the development of analytical approaches considering the risk associated with hazardous materials in railway transportation. We study three versions of trip plan problems in the presence of hazardous materials, denoted as hazardous materials trip plan problems. In the first part of this dissertation we incorporate the blocking and train makeup decisions into the hazardous materials trip plan generation process, while limiting the total population exposures and environmental damages below the given thresholds. In evaluating the risk, we use aggregate measures, i.e., population exposures and environmental damages. We propose a non-linear mixed integer programming formulation for the considered problem. The solution of the model is NP hard. In order to solve realistic size problem instances, a heuristic method is proposed by decomposing the problem into freight-to-block and block-to-train assignment problems. We then investigate more realistic hazardous materials trip plan problems by relaxing some of the assumptions. In the second part of this dissertation we incorporate risk-spreading functions into trip plan generation process and train scheduling decisions. For each risk spreading function, we present a mathematical formulation and then we design a heuristic method to solve realistic size problem instances. We continue this study by introducing joint hazardous material trip plan and pricing problems. We also relax the assumption of the information of the customer requests are known in advance. Accordingly, we introduce different categories of customers with the definition of specific treatment for each of them including accept/reject basis and particular delivery and price regulations. In particular, we grouped customer requests into two classes as follows: (a) traditional customers, who sign long term contracts with the carrier, must be fulfilled by the carrier’s own services, and their delivery and price quotations are set in advance and not subject to change; and (b) irregular customers, who make request for a carload moves less frequently and on an irregular basis, maybe outsourced/rejected because of (1) lack of train capacities, (2) additional risk exceeds the given risk thresholds, or (3) service level requirements. We propose two-phase heuristic to solve the considered problem. In the first phase, we solve a deterministic transportation planning and train timetabling problem for the known demands in advance. In the second phase, an optimization-based problem is built and solved at the arrival of the new request. Eventually, the dissertation ends with conclusion and further research recommendations

Hazardous Materials Transportation: a Literature Review and an Annotated Bibliography

The hazardous materials transportation poses risks to life, health, property, and the environment due to the possibility of an unintentional release. We present a bibliographic survey on this argument paying particular attention to the road transportation. We attempt to encompass both theoretical and application oriented works. Research on this topic is spread over the broad spectrum of computer science and the literature has an operations research and quantitative risk assessment focus. The models present in the literature vary from simple risk equations to set of differential equations. In discussing the literature, we present and compare the underlying assumptions, the model specifications and the derived results. We use the previous perspectives to critically cluster the papers in the literature into a classification scheme

Fairness in hazmat routing-scheduling: a bi-objective Stackelberg game

We investigate a hazmat routing-scheduling problem. To minimize the overall expected risk, various vehicles may take different routes/schedules to avoid multiple accidents on the same link. Therefore, the company envisages two issues: (1) unfairly, a vehicle departing earlier from its origin may arrive earlier at its destination than the others leaving later; (2) focusing only on the minimization of risk may increase travel time/cost incurred by the company. We suggest a bi-objective game-theoretic formulation and solve it by a modified Adaptive Large Neighborhood Search and Simulated Annealing. We test the solution on a real-life case and extract practical insights

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

A Dual Toll Policy for Regulating the Transportation of Hazardous Materials

The transportation of hazardous materials (hazmat) has drawn significant attention from various stakeholders due to the undesirable impacts on the environment and public health. Focusing on the connection between the traffic and the risk associated with the hazmat shipments, the present research aims to assist the regulator in designing a policy of dual tolls, imposed on both hazmat and non-hazmat shipments, to mitigate the hazmat risk in a road network. A bi-objective bi-level programming formulation is constructed. To be specific, the upper-level model indicates the regulator’s decision problem, minimizing the maximum link risk and the total network risk by imposing a dual-toll policy on any carrier. The lower level jointly considers the decisions of multiple hazmat carriers and non-hazmat travelers, minimizing the total transportation cost, including the toll cost. (By “non-hazmat traveler", we mean both people who carry and do not carry products.) Given the bi-level structure and the non-linear nature, a solution procedure with two parts is designed. First, we develop two alternative linearization approaches. One is piecewise linearization, transforming the non-linear terms into linear ones. The other applies the Frank-Wolfe algorithm, an iterative first-order optimization algorithm. Then a genetic-algorithm-based methodology will integrate both levels. Computational experiments on different sizes of networks are performed to demonstrate the effectiveness of the model. Various analyses, involving trade-offs, sensitivities, and examination of convergence, are conducted to provide additional managerial insights. These can be used to facilitate stakeholders’ decision making