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Nebojsa J Bojovic - One of the best experts on this subject based on the ideXlab platform.
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A stochastic model predictive control to heterogeneous Rail Freight car fleet sizing problem
Transportation Research Part E: Logistics and Transportation Review, 2015Co-Authors: Miloš Milenković, Nebojsa J Bojovic, Libor Švadlenka, Vlastimil MelicharAbstract:In this paper a rolling horizon approach is applied for simultaneous optimization of the Rail Freight car fleet size and allocation problem. Developed dynamic model of loaded and empty Rail Freight car flows explicitly treats state, control and station capacity constraints in presence of various Freight car types under the partial substitutability among them. Demands and traveling times are considered as random variables. Proposed approach is applied to a set of test cases and it shown to be successful, ultimately providing a new managerial tool for more effective and efficient planning and analyzing Rail Freight car fleets.
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A fuzzy random model for Rail Freight car fleet sizing problem
Transportation Research Part C: Emerging Technologies, 2013Co-Authors: Miloš Milenković, Nebojsa J BojovicAbstract:Abstract In the area of Freight transport, the Railroads of almost all countries face with strong competition and a prominent trend of market reduction. It has become imperative for Rail systems to develop better planned instruments for more rational and efficient utilization of Freight cars that represent a great amount of total investments. In this paper a new formulation and a solution procedure is proposed for optimizing the fleet size and Freight car allocation in the presence of uncertainty. The uncertainty of the Rail Freight car demand is often tackled from the traditional probability theory. However, various types of uncertainties and fuzziness are inherent in real Rail Freight transport operating environment. In this paper, the issue of Rail Freight car fleet sizing and allocation problem will be addressed under such circumstances. Specifically, an approach based on optimal control theory by considering the fuzziness and randomness for Rail Freight car demand is developed here. The problem is formulated as the problem of finding an optimal fuzzy regulator for a fuzzy linear system with fuzzy quadratic performance index and fuzzy random initial conditions. Numerical example is given to illustrate the model and solution methodology.
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A Two-Level Approach to the Problem of Rail Freight Car Fleet Composition
TRANSPORT, 2010Co-Authors: Nebojsa J Bojovic, Miloš Milenković, Branislav Boskovic, Aleksandar SunjicAbstract:Abstract One of the main objectives for a Rail company is to minimize the size of Rail Freight car fleet in order to reduce operating costs. The problem of Rail Freight car fleet composition is aimed at determining an optimal structure and size of Freight car fleet in order to respond to actual transport demand. A Rail company must have capabilities to respond to actual transport demand in case it wants to increase the level of competitiveness on the transport market. Therefore, it is necessary that the structure and size of Rail Freight car fleet correspond to the structure and size of Rail transport demand. In this paper, we developed a two‐level approach to determining an optimal Rail Freight car fleet composition. This approach has been tested for the case of the Public Enterprise ‘Serbian Railways’ and the obtained results show the potential for a practical application of the proposed approach.
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a general system theory approach to Rail Freight car fleet sizing
European Journal of Operational Research, 2002Co-Authors: Nebojsa J BojovicAbstract:Abstract The transportation of goods from shippers to consignees is a Railroad's major activity. Rail Freight cars are enormously expensive and a Rail vehicle fleet represents one of the largest capital resources of most Railroads. Resource allocation to Rail Freight cars is an extraordinary complex managerial problem. This paper describes the determination of an optimal number of Rail Freight cars so as to satisfy the demand, on one hand, and minimize the total cost, on the other. A new mathematical model relying on optimal control theory is developed. The problem is formulated as the problem of finding an optimal regulator for a linear system, excited by Gaussian white noise, a quadratic performance index, and random initial conditions. The model has been tested on numerical examples.
Miloš Milenković - One of the best experts on this subject based on the ideXlab platform.
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A stochastic model predictive control to heterogeneous Rail Freight car fleet sizing problem
Transportation Research Part E: Logistics and Transportation Review, 2015Co-Authors: Miloš Milenković, Nebojsa J Bojovic, Libor Švadlenka, Vlastimil MelicharAbstract:In this paper a rolling horizon approach is applied for simultaneous optimization of the Rail Freight car fleet size and allocation problem. Developed dynamic model of loaded and empty Rail Freight car flows explicitly treats state, control and station capacity constraints in presence of various Freight car types under the partial substitutability among them. Demands and traveling times are considered as random variables. Proposed approach is applied to a set of test cases and it shown to be successful, ultimately providing a new managerial tool for more effective and efficient planning and analyzing Rail Freight car fleets.
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A fuzzy random model for Rail Freight car fleet sizing problem
Transportation Research Part C: Emerging Technologies, 2013Co-Authors: Miloš Milenković, Nebojsa J BojovicAbstract:Abstract In the area of Freight transport, the Railroads of almost all countries face with strong competition and a prominent trend of market reduction. It has become imperative for Rail systems to develop better planned instruments for more rational and efficient utilization of Freight cars that represent a great amount of total investments. In this paper a new formulation and a solution procedure is proposed for optimizing the fleet size and Freight car allocation in the presence of uncertainty. The uncertainty of the Rail Freight car demand is often tackled from the traditional probability theory. However, various types of uncertainties and fuzziness are inherent in real Rail Freight transport operating environment. In this paper, the issue of Rail Freight car fleet sizing and allocation problem will be addressed under such circumstances. Specifically, an approach based on optimal control theory by considering the fuzziness and randomness for Rail Freight car demand is developed here. The problem is formulated as the problem of finding an optimal fuzzy regulator for a fuzzy linear system with fuzzy quadratic performance index and fuzzy random initial conditions. Numerical example is given to illustrate the model and solution methodology.
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A Two-Level Approach to the Problem of Rail Freight Car Fleet Composition
TRANSPORT, 2010Co-Authors: Nebojsa J Bojovic, Miloš Milenković, Branislav Boskovic, Aleksandar SunjicAbstract:Abstract One of the main objectives for a Rail company is to minimize the size of Rail Freight car fleet in order to reduce operating costs. The problem of Rail Freight car fleet composition is aimed at determining an optimal structure and size of Freight car fleet in order to respond to actual transport demand. A Rail company must have capabilities to respond to actual transport demand in case it wants to increase the level of competitiveness on the transport market. Therefore, it is necessary that the structure and size of Rail Freight car fleet correspond to the structure and size of Rail transport demand. In this paper, we developed a two‐level approach to determining an optimal Rail Freight car fleet composition. This approach has been tested for the case of the Public Enterprise ‘Serbian Railways’ and the obtained results show the potential for a practical application of the proposed approach.
Vlastimil Melichar - One of the best experts on this subject based on the ideXlab platform.
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A stochastic model predictive control to heterogeneous Rail Freight car fleet sizing problem
Transportation Research Part E: Logistics and Transportation Review, 2015Co-Authors: Miloš Milenković, Nebojsa J Bojovic, Libor Švadlenka, Vlastimil MelicharAbstract:In this paper a rolling horizon approach is applied for simultaneous optimization of the Rail Freight car fleet size and allocation problem. Developed dynamic model of loaded and empty Rail Freight car flows explicitly treats state, control and station capacity constraints in presence of various Freight car types under the partial substitutability among them. Demands and traveling times are considered as random variables. Proposed approach is applied to a set of test cases and it shown to be successful, ultimately providing a new managerial tool for more effective and efficient planning and analyzing Rail Freight car fleets.
Peter Endemann - One of the best experts on this subject based on the ideXlab platform.
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Online Rail Freight Exchange (ORFE): Better Rail Competitiveness and Acceptance
Integrated Spatial and Transport Infrastructure Development, 2016Co-Authors: Peter EndemannAbstract:In many European countries, Rail Freight demand has increased considerably during the last 10–15 years. A closer look at the German case reveals that—given a considerable amount of empty wagons and an untransparent market—there is still some potential to increase efficiency and competitiveness of Rail Freight and to overcome knowledge and information barriers in the Rail Freight market. Embedded in the CODE24 strategy, an online Rail Freight exchange (ORFE) is a useful instrument to cope with these challenges. ORFE is a market platform where Rail Freight services are offered and requested on-line. Besides some initial business and case studies, the market’s relevance of such a tool and the requirements of potential users—predominantly shipping companies, transport logistics providers and Rail operators—had to be explored. Therefore, a workshop was held with these groups and other experts in 2011. Based on the outcome, potential operators had to be identified. In September 2012, CODE24 identified two companies who were interested in cooperating with the CODE24 network and developing such an online Rail market ready for commercialisation. CODE24 decided to support both companies and emphasize their neutrality. The first platform is “Railcargo-online” ( http://www.Railcargo-online.com ), the second platform is “freit-one” ( http://www.freit-one.de ). The latter uses the software prototype developed in CODE24. Both platforms are available since October 2013 and were presented at a joint workshop with the INTERREG-IVB programme in November 2013. A preliminary appraisal by February 2014 showed that both platforms are working well and count up to 80 registered companies. This paper uses metric tons throughout.
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Online Rail Freight Exchange (ORFE): Better Rail Competitiveness and Acceptance
Integrated Spatial and Transport Infrastructure Development, 2016Co-Authors: Peter EndemannAbstract:In many European countries, Rail Freight demand has increased considerably during the last 10–15 years. A closer look at the German case reveals that—given a considerable amount of empty wagons and an untransparent market—there is still some potential to increase efficiency and competitiveness of Rail Freight and to overcome knowledge and information barriers in the Rail Freight market.
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Enhancing Rail Competitiveness with Online Rail Freight Exchange
Transportation Research Record, 2015Co-Authors: Peter EndemannAbstract:In many European countries, Rail Freight demand has increased considerably during the past 10 to 15 years though only a few countries have reached considerable levels such as those observed in the United States. A closer look at the German case reveals that, given a considerable amount of empty wagons and a nontransparent market, there is still some potential to increase efficiency and competitiveness of Rail Freight and to overcome knowledge and information barriers in the Rail Freight market. Embedded in the strategy of the transnational project titled “CODE 24” (Corridor 24 Development Rotterdam–Genoa), an online Rail Freight exchange appears to be the appropriate instrument to cope with these challenges. The exchange is a market platform through which Rail Freight services are offered and requested online. At the start of the project, except for some initial business and case studies, the market relevance of such a tool and the requirements of potential users (predominantly shipping companies, transpo...
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CODE 24 Online Rail Freight Exchange - Needs of Potential Users
2012Co-Authors: Peter Endemann, Karl Tracksdorf, Thomas KasparAbstract:Drawing on some basic application of economic theory and an appreciation of how decisions are made when transporting goods over land, an interactive online market platform is suggested as a means of overcoming information barriers in the Rail Freight market. The article explores the rationale for an online Rail Freight exchange and highlights its role as part of the wider European Union funded Project CODE 24, which is aimed at developing the Trans-European corridor no. 24, Rotterdam-Genoa.
Angélique Léonard - One of the best experts on this subject based on the ideXlab platform.
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Life cycle assessment of Rail Freight transport in Belgium
Clean Technologies and Environmental Policy, 2020Co-Authors: Angel L. Merchan, Sandra Belboom, Angélique LéonardAbstract:The objective of this paper is to determine the environmental impact of Rail Freight transport in Belgium using the life cycle assessment (LCA) methodology. The study includes the assessment of diesel trains, electric trains and Rail Freight transport considering the Belgian traction mix. Moreover, a comparison of the environmental impacts of electric trains using the electricity supply mix of different European countries has been performed. The Rail Freight transport system has been divided into three sub-systems: Rail transport operation, Rail equipment and Rail infrastructure. The system approach of the LCA methodology involves studying both the direct processes connected with the transport activity (e.g. energy consumption or direct emissions), as well as other necessary elements for Rail transport such as energy production, rolling stock and Railway infrastructure. A comprehensive study of the Belgian Railway network has been performed, collecting country-specific data on the construction, maintenance and disposal of infrastructure. Electric trains present a better environmental performance than diesel trains in Belgium. For example, the use of electric trains (using the Belgian electricity supply mix of 2012) rather than diesel trains represents a reduction of 26% of environmental impact on climate change. The electricity supply mix contributes significantly to the environmental performance of electric trains. As the use of electric trains increases in future, the energy split for the electricity generation will be more important in the environmental impacts of goods transport. The increased use of electric trains represents an opportunity to attain a more environmentally and energy-efficient Rail Freight transport system, especially when they are powered by sustainable electricity. Graphic abstract
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A road map for explorative scenario creation on Belgian Rail Freight transport development
2017Co-Authors: Frank Troch, Sandra Belboom, Thierry Vanelslander, Christa Sys, Florent Laroche, Angel Merchan, Martine Mostert, Vidar Stevens, Christine Maher Fouad Tawfik, Angélique LéonardAbstract:The starting point of this article is the weak usage of Rail Freight in Belgium and Europe, both as a sustainable mode of land transportation in itself as well as a part of the intermodal chain. The results are obtained by transversal research on Rail Freight transport in Belgium, taking into account the European context. This interdisciplinary research develops a road map for the creation of three integrated scenarios: a best case, medium case and worst case scenario for Rail Freight development, based on a detailed SWOT (strength, weakness, opportunities, threats) analysis. It includes the most probable future developments for Rail Freight transport and hinterland connections. These developments are obtained from literature review and discussions with a heterogeneous panel of experts in the fields of (i) optimal corridor and hub development, (ii) macroeconomic impact, (iii) sustainability, (iv) effective market regulation and (v) governance and organization for a well-functioning intermodality. The Delphi approach is used in combination with a survey analysis. Frequency tables and the H-index allow defining a ranking and selection of SWOT elements. The obtained scenarios allow future research to quantify and measure the impact of future developments and decisions towards the Belgian Rail Freight market.
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Rail Freight intermodality in Belgium: energy related emissions
2016Co-Authors: Angel Merchan Arribas, Sandra Belboom, Angélique LéonardAbstract:BRAIN-TRAINS is a project that deals with the possible development of Rail Freight intermodality in Belgium. Life Cycle Assessment methodology has been used to analyse the sustainability impact of Rail Freight intermodality for 3 divergent Belgian scenarios by 2030. This objective is directly linked to the goal of increasing the Rail market share by 2030, stated by European Commission’s White Paper on transport (2011). Department of Chemical Engineering – PEPs, Products, Environment, Processes University of Liege, Allee du six aout 11 Bat B6a (Sart-Tilman) 4000 Liege, Belgium. a.merchan@ulg.ac.be
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Environmental impact assessment of Rail Freight intermodality
Proceedings of the Third International Conference on Railway Technology: Research Development and Maintenance, 1Co-Authors: Angel Merchan Arribas, Sandra Belboom, Angélique LéonardAbstract:The European Commission's White Paper on transport (European Commission, 2011) seeks to achieve an efficient and sustainable balance between the various transport modes. Environmental impact studies on intermodality transport show that Rail Freight transport is the land-based transport that has a higher environmental performance compared to intermodal road-Rail and all-road transport (Fries and Hellweg, 2014), especially when electrified Railway is used (Spielmann and Scholz, 2005). Life Cycle Assessment (LCA) methodology allows us to model as best as possible the environmental impacts of several pollutants in numerous categories. For other categories such as accident damages, noise impact and land use, new developments have to be performed. For the environmental impact assessment, all life cycle phases of Rail Freight transport operation, Rail infrastructure, and Rail equipment are taken into account (Spielmann et al., 2007).
