The Short-term Car Flow Planning Model in Rail Freight Company – Case Study

AbstractWith the promotion of the environmentally friendly transportation modes (the European Commission supports the freight transport operations in the rail sector), an increase in the diversification of the demand is observed. While most rail freight companies tend to apply fixed schedules, this approach is not effective turns out to be ineffective due to the need to meet the customer's specific requirements.The purpose of this paper is to present a case study of empty wagon flow planning over a medium term horizon and to discuss the opportunities of improvement of this plans by discrete optimization. In order to increase the utilization and availability of wagons, the planning procedure with a rolling horizon has to be implemented. Unfortunately, since the plan has to be updated ca. every 4hours, this planning approach needs effective optimization tools. Our hybrid two-stage approach is designed to be implemented in such business environment. This formulation allows us to solve real life instances even for a 7-day time horizon

Imitation forecast of railway system operation in a macroregion

The article describes an analytical and information system that was used for forecasting the operation parameters of the railway system in a macroregion of Russia - the Far North. Its economy is focused on the extraction and processing of hydrocarbons, metal production, construction materials, and generate large volumes of exports and inter-regional cargo flows. The region covers an expansive territory and is characterized by harsh weather, an extreme environment, and uneven development of the transportation network. Research into the transportation issues of economic development in such areas presents a challenging task because the region is unique, statistical data are incomplete and classified; there is a hierarchy of businesses and organizations operating in the region that have their own goals and objectives and compete against its other; the region is plagued with social and environmental problems and a lack of administrative integration between individual districts. Using rigorous mathematical tools for assessing transportation infrastructure projects under such conditions is only limited to finding solutions to stand-alone problems and scenario comparison. A model of the applied system that is outlined in the article makes it possible to analyze specific projects of regional railway system development that take into account strategic priorities and goals of the state, social and economic development problems experienced by the neighboring regions, the oil and gas sector and major employers, as well as corporate goals of the sustainable development of railway companies. The application of the model over an extended period of time showed that the analysis of the structure of cargo flows and customers bound to junctions of the transportation network makes it possible to suggest what aspects of the railway infrastructure should be reorganized in line with the development dynamics of economic entities that consume transportation services. The study is built upon a number of projects that were implemented in the north of Tyumen Region and the Yamal- Nenets and Khanty-Mansi autonomous areas of Russia. © 2018 WIT Press.ACKNOWLEDGEMENT The work was supported by Act 211 Government of the Russian Federation, contract № 02.A03.21.0006

A Category Classification Based Safety Risk Assessment Method for Railway Wagon Loading Status

The identification and control of safety risks in the loading state of goods wagon is one of the important tasks to ensure the safety of goods in transit. In view of the problem that the current risk assessment of transportation schemes is mainly based on manual experience and cannot be quantified, which makes it difficult to accurately determine the safety risk of transportation on the way, a risk assessment method for loading status of goods wagon based on scenario classification was proposed. Firstly, based on a detailed analysis of the safety risk points in various stages of railway freight operations, a SHEL influencing factor model based on scenario classification was constructed. Then, considering the characteristics of railway freight transportation, a fuzzy accident tree model (FTA) of goods wagon loading state risk was constructed, and the fault tree was transformed into a Bayesian network structure according to the mapping algorithm of fuzzy fault tree and Bayesian. Furthermore, a triangular fuzzy membership function was introduced to describe the fault probability of nodes, and a BN based fuzzy fault tree inference algorithm was proposed. Finally, taking a railway station and route transporting coil steel goods in China as an example, this paper explained how to integrate expert knowledge through fault tree and Bayesian network to support railway freight scheme designers in conducting risk quantification assessment of freight wagon loading status

Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

Transportation Systems Analysis and Assessment

The transportation system is the backbone of any social and economic system, and is also a very complex system in which users, transport means, technologies, services, and infrastructures have to cooperate with each other to achieve common and unique goals.The aim of this book is to present a general overview on some of the main challenges that transportation planners and decision makers are faced with. The book addresses different topics that range from user's behavior to travel demand simulation, from supply chain to the railway infrastructure capacity, from traffic safety issues to Life Cycle Assessment, and to strategies to make the transportation system more sustainable

Evaluation et gestion de la flexibilité dans les chaînes logistiques : nouveau cadre général et applications

This thesis focuses on flexibility issues in supply chain. These issues are becoming more and more important for firms because of the increasingly changing business environment and customer behaviors. Although some of these issues have been tackled in academic research in recent years, but studies have mainly concentrated in conceptual levels and there is little consensus even on the definition of flexibility. This thesis aims at defining a new framework for the supply chain flexibility, proposing quantitative measures of the flexibility and optimizing the use of flexibility, especially in an integrated production and transportation planning context. The new framework of supply chain flexibility is based on classification of different flexibility aspects in a supply chain into three main categories - manufacturing flexibility,logistic chain flexibility and system flexibility. These flexibility types are further distinguished into major flexibility dimension and other flexibility dimension.In order to measure supply chain flexibility from a quantitative point of view, Mechanical Analogy method is particularly discussed. A procedure is established to enlarge and carry out this method in supply chain, provided with a case study to evaluate the flexibility of Louis Vuitton stores.One of the most important issues is to optimally make use of the available flexibility. We investigate an Integrated Production and Transportation Planning problem with given flexibility tolerances, where the production and transportation activities are intimately linked to each other and must be scheduled in a synchronized way. Particularly, heterogeneous vehicles are taken into account. Two mixed integer linear programming models are constructed.Three algorithms are developed and compared with linear relaxation bounds for large sized real life instances and with optimal solutions for small sized instances. These comparisons show the effectiveness of our heuristics in solving real life problemsCette thèse étudie la problématique de la flexibilité dans les chaînes logistiques. La recherche académique a commencé à s’intéresser à cette problématique depuis quelques années, mais les études existantes restent pour la plupart au niveau conceptuel et il y a peu de consensus sur la définition même de la flexibilité. Cette thèse a pour ambition de définir un nouveau cadre pour la flexibilité dans les chaînes logistiques, proposer des mesures quantitatives pour la flexibilité et enfin optimiser l’utilisation de la flexibilité, en particulier dans un contexte de planification intégrée de la production et du transport.Ce travail de thèse vise tout d’abord à établir un nouveau cadre pour la flexibilité de la chaîne logistique, où les différents aspects de la flexibilité sont classifiés en trois catégories principales: flexibilité de la production, flexibilité de la chaîne logistique et flexibilité du système. Dans chacune de ces catégories, on peut trouver des dimensions primordiales et des dimensions moins importantes.Afin d’évaluer la flexibilité de manière quantitative, nous faisons appel à la méthode Analogie Mécanique. Cette méthode propose une analogie entre un système mécanique vibratoire et une chaîne logistique. Dans ce contexte, nous avons développé une étude de cas pour Louis Vuitton afin d’évaluer la flexibilité de leurs magasins, et nous avons établi une procédure pour implémenter cette méthode.Une autre problématique importante est l’utilisation optimale de la flexibilité existante.Nous nous sommes particulièrement intéressés à la planification intégrée de la production et du transport avec des flexibilités sur la capacité de transport, où la production et le transport sont intimement liés du fait du manque de capacité de stockage et doivent être planifiées conjointement. Particulièrement, les véhicules hétérogènes sont pris en compte.Nous avons construit deux modèles de programmation linéaire en nombres mixtes et développé trois algorithmes qui ont été comparées par rapport à la relaxation linéaire pour les instances de grande taille et aux solutions optimales pour des instances de petite taille. Ces comparaisons montrent que les heuristiques proposées sont efficaces pour résoudre des problèmes réels, aussi bien en termes de qualité de solution qu’en termes de temps de calcul

Using Optimisation and Machine Learning to Validate the Value of Infrastructure Investments

When stakeholders commit to building infrastructure as part of strategic, long-term planning, the final facilities are not normally amenable to modification after completion. A consequence of this is that users are forced to operate within the original specifications for, at least, as long as it takes to carry out major refurbishments or retrofitting, and even then, the constraints imposed by the original layout may be inescapable. On one hand, the original infrastructure plans enhance (or limit) the users' ability to operate efficiently for years to come. As time passes and the payback period approaches, changing operating conditions and unforeseen bottlenecks in the original blueprint can, at best, affect the economic returns and, at worst, defeat the purpose of the whole project (see, for example, Castellon airport in Spain, which was built but is grossly underutilised), producing unanticipated economical, social and political repercussions. On the other hand, managers and operators (that is, those living with the consequences of the strategic planning) have some leeway to compensate for miscalculations by means of their tactical and operational planning. In this chapter, we explore the use of quantitative techniques to, first, amend bottlenecks and uncertain market and operating conditions that affect the performance of infrastructure investments (the tactic and operational levels), and second, validate the effectiveness of the original infrastructure design (the strategic level) under these changing conditions. More specifically, we present a rail scheduling case study where we combine demand forecasting using Machine Learning techniques and formal Operations Research methods to assess and maximise the value of already-existing infrastructure. Rail scheduling is a typical optimisation problem popular in the literature, but its potential value is bounded not only by its technical properties and specifications (how good the algorithm is) but also by the accuracy of data feeding the algorithm. Such data is critical in specifying the demand that a facility will experience in the future, and the costs that will be incurred to operate it. The use of intensive data analytics and appropriate Machine Learning techniques can resolve this and provide a substantial competitive edge for investors and operators of rail inter-modal terminals. We anticipate that Machine Learning algorithms that predict future demand, coupled with optimisation techniques that streamline operations of facilities, can be integrated to create tools that help policy makers and terminal operators maximise the value of their current infrastructure, while meeting ever-changing demand

RISK MITIGATION CAPABILITY OF FLEXIBILITY PERFORMANCE CONTRACTS FOR DEMAND RESPONSE IN ELECTRICITY SYSTEMS

The transition of the energy system increases the urgency to cope with the intermittency of renewable energy sources to keep the electricity network balanced. Demand Response (DR) measures are a promising approach to align the electricity consumption, especially of industrial consumers, with current electricity supply. While adequate information systems (IS) are already in place to dynamically adapt electricity consumption patterns, industrial consumers are still reluctant to implement DR measures due to uncertainty of their financial performance. Nevertheless, studies on risk transfer instruments related to DR investments are still scarce. To con-tribute to the closure of this research gap, we examine the risk transfer capability of Flexibility Performance Contracts (FPC). We derive cash flow structures for representative FPC designs, calculate risk premiums and enable the comparison of corresponding risk profiles. Presented FPCs are evaluated based on a real-world industrial use case. Thereby, the financial perfor-mance is modelled stochastically, taking electricity price fluctuation, industrial process charac-teristics and IS-backed decisions into account. Our results reveal that FPCs represent well-suited risk transfer instruments for DR measures. Thus, FPCs have the potential to accelerate the application of DR measures and therefore to complement existing capabilities of IS in the context of electricity networks

Towards Sustainable Freight Energy Management - Development of a Strategic Decision Support Tool

Freight transportation, in its current shape and form, is on a highly unsustainable trajectory. Global demand for freight is ever increasing, while this demand is predominantly serviced by inefficient, fossil fuel dependent transportation options. The management of energy use in freight transportation has been identified as a significant opportunity to improve the sustainability of the freight sector. Given the vast amount of energy mitigation measures and policies to choose from to attempt this, decision-makers need support and guidance in terms of selecting which policies to adopt – they are faced with a complex and demanding problem. These complexities result, in part, from the vast range, scope and extent of measures to be considered by decision-makers. The tool developed needs to encompass a suitable methodology for comparing proverbial apples to oranges in a fair and unbiased manner, despite the development of one consistent assessment metric that can accommodate this level of diversity being problematic. Further to this, decision-makers need insight into the extent of implementation that is required for each measure. Because the level of implementation of each measure is variable and the extent to which each adopted measure will be implemented in the network needs to be specified, the number of potential measure implementation combinations that decision-makers need to consider is infinite, adding further complexity to the problem. Freight energy management measures cannot, and should not, be evaluated in isolation. The knock-on effects of measure adoption on the performance of other measures need to be considered. Measures are not all independent and decision-makers need to take these dependencies and their ramifications into account. In addition, there is dimensionality to be accounted for in terms of each measure, because one measure can be applied in a variable manner across different components of the freight network. A unique and independent decision needs to be made on the application of a measure for each of these network components (for example for each mode). Decisions on freight transportation impact all three traditional pillars of sustainability: social, environmental and economic. Measure impacts, thus, need to be assessed over multiple criteria. Decisions will affect a variety of stakeholders and outcomes must be acceptable to a range of interested parties. Sustainability criteria are often in conflict with one another, implying that there are trade-offs to be negotiated by the decision-makers. Decision-makers, thus, need to propose system alterations, or a portfolio of system alterations, that achieve improvements in some sustainability respects, whilst maintaining a balance between all other sustainability aspects. Moreover, the magnitude of impacts (be it positive or negative) of a measure on the sustainability criteria is variable, adding additional dimensionality to the problem. The aim of the research presented in this dissertation was to develop a decision support tool which addresses the complexities involved in the formulation of freight transport energy management strategies on behalf of the decision-makers, facilitating the development of holistic, sustainable and comprehensive freight management policy by government level decision-makers. The Freight Transport Energy Management Tool (FTEMT) was developed in response to this research objective, using a standardised operations research approach as a roadmap for its development. Following a standardised operations research approach to model development provides a structure where stakeholder participation can be encouraged at all the key stages in the decision-making process; it offers a logical basis for proposing solutions and for assessing any proposed suggestions by others; it ensures that the appraisal of alternative solutions is conducted in a logical, consistent and comprehensive manner against the full set of objectives; and it provides a means for assessing whether the implemented instruments have performed as predicted, enabling the improvement of the model being developed. The FTEMT can be classified as a simulation optimisation model, which is a combination between multi-objective optimisation and simulation. The simulation component provides a suitably accurate representation of the freight system and affords the ability to approximate the effect that measure implementation will have on the sustainability objectives, whilst the optimisation component provides the ability to effectively explore the decision space and reduces the number of alternative options (and, therefore, the complexity) that decision-makers need to consider. It is this simulation optimisation backbone of the FTEMT that enables the tool to address all the complexities surrounding the problem, enabling the decision support produced by the FTEMT to provide the information necessary for decision-makers to steer the freight transport sector towards true sustainability. Although this problem originates from the domain of sustainable transportation planning, the combination of operations research and transport modelling knowledge applied proved essential in developing a decision support tool that is able to generate adequate decision support on the problem. To demonstrate the use and usefulness of the decision support system developed, a fictitious case study version of the FTEMT was modelled and is discussed throughout this dissertation. Results from the case study implementation were used to verify and validate the tool, to demonstrate the decision support generated and to illustrate how this decision support can be interpreted and incorporated into a decision-making process. Outputs from the case study FTEMT proved the tool to be operationally valid, as it successfully achieved its stated objectives (the FTEMT unearths a Pareto set of solutions close to the true efficient frontier through the exploration of different energy management measure combinations). Explained in short, the value of using the FTEMT to generate decision support is that it explores the decision space and reduces the number of decision alternatives that decision-makers need to consider to a manageable number of solutions, all of which represent harmonic measure combinations geared toward optimal performance in terms of the entire spectrum of the problem objectives. These solutions are developed taking all the complexity issues surrounding the problem into account. Decision-makers can, thus, have confidence that the acceptance of any one of the solutions proposed by the FTEMT will be a responsible and sound decision. As an additional benefit, preferences and strategic priorities of the decision-makers can be factored in when selecting a preferred decision alternative for implementation. Decision-makers must debate the trade-offs between solutions and need to determine what they are willing to sacrifice to realise what gain, but they are afforded the opportunity to select solutions that show the greatest alignment with their official mandates. The structure of the FTEMT developed and described in this dissertation presents a practical methodology for producing decision support on the development of sound freight energy management policy. This work serves as a basis to stimulate further scholarship and expands upon the collective knowledge on the topic, by proposing an approach that is able to address the full scale of complexities involved in the production of such decision support