Manish Verma

A lead-time based approach for planning rail–truck intermodal transportation of dangerous goods

The remarkable growth in intermodal transportation over the past two decades has not been matched by a comparable level of academic activity, especially in the context of transporting hazardous materials (hazmats). In this paper, we present a first attempt for the development of an analytical framework for planning rail-truck intermodal transportation of hazmats. A bi-objective optimization model to plan and manage intermodal shipments is developed. To represent the current practice, the routing decisions in the model are driven by the delivery-times specified by the customers. An iterative decomposition based solution methodology which takes advantage of the problem structure is provided. A realistic problem instance based on the intermodal service network in eastern US is solved. This framework is used for developing a number of managerial insights, and for generating elements of the risk-cost frontier.

A Tactical Planning Model for Railroad Transportation of Dangerous Goods

Railroad transportation of hazardous materials did not receive as much attention as highway transportation in the academic literature, although comparable volumes are shipped via these two transport modes in North America and Europe. In this paper, we present an optimization methodology for the railroad tactical planning problem with risk and cost objectives. We determine the routes to be used for each shipment, the yard activities, and the number of trains of different types needed in the network. The transport risk assessment component of our model incorporates the differentiating characteristics of railroad operations. We develop a memetic algorithm-based solution methodology, which combines genetic and local searches, to solve the biobjective model. The railroad infrastructure in the midwestern United States is used as a basis for generating problem instances of the size encountered in real life. Our analyses of the solutions of instances indicate that it is possible to achieve significant reductions in population exposure without incurring unacceptable increases in operational costs.

Transport Mode Selection for Toxic Gases: Rail or Road?

A significant majority of hazardous materials (hazmat) shipments are moved via the highway and railroad networks, wherein the latter mode is generally preferred for long distances. Although the characteristics of highway transportation make trucks the most dominant surface transportation mode, should it be preferred for hazmat whose accidental release can cause catastrophic consequences? We answer this question by first developing a novel and comprehensive assessment methodology-which incorporates the sequence of events leading to hazmat release from the derailed railcars and the resulting consequence-to measure rail transport risk, and second making use of the proposed assessment methodology to analyze hazmat transport risk resulting from meeting the demand for chlorine and ammonia in six distinct corridors in North America. We demonstrate that rail transport will reduce risk, irrespective of the risk measure and the transport corridor, and that every attempt must be made to use railroads to transport these shipments.

An expected consequence approach to route choice in the maritime transportation of crude oil.

Maritime transportation is the major conduit of international trade, and the primary link for global crude oil movement. Given the volume of oil transported on international maritime links, it is not surprising that oil spills of both minor and major types result, although most of the risk-related work has been confined to the local settings. We propose an expected consequence approach for assessing oil-spill risk from intercontinental transportation of crude oil that not only adheres to the safety guidelines specified by the International Maritime Organization but also outlines a novel technique that makes use of coarse global data to estimate accident probabilities. The proposed estimation technique, together with four of the most popular cost-of-spill models from the literature, were applied to study and analyze a realistic size problem instance. Numerical analyses showed that: a shorter route may not necessarily be less risky; an understanding of the inherent oil-spill risk of different routes could potentially facilitate tanker routing decisions; and the associated negotiations over insurance premium between the transport company and the not-for-profit prevention and indemnity clubs. Finally, we note that only the linear model should be used with one of the three nonlinear cost-of-spill models for evaluating tanker routes.

Railroad Transportation of Hazardous Materials: Models for Risk Assessment and Management

A significant portion of hazardous materials (hazmat) is transported via railroads, and this chapter is the first attempt at capturing and assimilating the work done in this domain. To facilitate a better understanding of the building blocks, the chapter starts with a description of a typical freight rail transportation system, which in turn sets the stage for the introduction of different risk assessment methodologies and risk management techniques. Three of the most popular measures of hazmat transport risk, i.e., expected consequence, incident probability, and population exposure—with appropriate adaptations to incorporate the dynamics of railroad operations—are developed. Discussion on risk management is mostly focused on optimization frameworks developed for solving tactical planning problems, and some discussion on tank-car design and hazmat railcar placement in a train-consist. Finally, we outline some research issues requiring further investigation, and motivate the need for adopting a multidisciplinary approach.

Minimal-degree coprime factorizations of rational matrix functions

Abstract We describe coprime factorizations of rational matrix functions that have the degree of nonminimality as small as possible. The description is based on state-space representations. The recently developed theory of common minimal divisors of rational matrix functions serves as a main tool in the proofs.

A routing and scheduling approach to rail transportation of hazardous materials with demand due dates

This paper investigates the routing and scheduling of rail shipments of hazardous materials (hazmat) in the presence of due dates. In particular, we consider the problem of minimizing the weighted sum of earliness and tardiness for each demand plus the holding cost at each yard, while forcing a risk threshold on each service leg at any time instant. The Federal Railroad Administration (FRA) accident records, between 1999 and 2013, were analyzed to establish that train speed was the most significant factor in derailment. A mixed-integer programming model and a heuristic-based solution method are proposed for preparing the shipment plan. Finally, the analytical framework is used to study and analyze a number of realistic-sized problem instances generated using the infrastructure of a Class I railroad operator.

An analytical framework for integrated maritime terminal scheduling problems with time windows

Container transport, an integral part of intercontinental trade, has steadily increased over the past few decades. The productivity of such a system, in part, hinges on the efficient allocation of terminal resources such that the container transit time is minimized. This study provides an analytical framework, which entails efficient scheduling of quay and yard cranes, to minimize the time spent by containers at a terminal. A mixed-integer programming model is developed to capture the two-stage multi-processor characteristic of the problem, where each crane has specific time window availability. A genetic algorithm equipped with a novel decoding procedure is developed. The mixed-integer model is tested on a number of problem instances of varying sizes to gain managerial insights.

A periodic planning model for maritime transportation of crude oil

Crude oil is primarily transported through sea using very large tankers. Efficient scheduling of these tankers is challenging as well as critical given long lead times, tight delivery time windows and high operational costs. We attempt to solve such a scheduling problem for an oil supplier facing supply quota and port capacity constraints. A mixed-integer programming formulation and two time-dependent solution techniques are proposed. Numerical results suggest that computing time was a function of the number, starting location, and time to availability of tankers at the supply sources. Finally, a time-based decomposition technique is presented to solve large problem instances, illustrating substantial reductions in computing time for marginally worse-off solutions.

An analytical approach to the protection planning of a rail intermodal terminal network

Rail-truck intermodal transportation has experienced remarkable growth over the past three decades, and plays a vital role in the freight transportation system in North America. Hence, a crucial issue is to guarantee continuity of service and to minimize the adverse impacts following disruption, natural or man-made. We make the first attempt to develop an analytical framework that could be used by rail intermodal owners to determine the best fortification plan in order to minimize the impact of a worst-case attack. The complexity of the resulting tri-level mathematical model motivated the development of a decomposition-based heuristic solution technique, and the resulting analytical approach was used to solve and analyze problem instances generated using the realistic infrastructure of a railroad operator.