Optimization Models for Rail Car Fleet Management

1st Edition - September 7, 2019
Authors: Milos Milenkovic, Nebojsa Bojovic
Language: English
Paperback ISBN:
9 7 8 - 0 - 1 2 - 8 1 5 1 5 4 - 9
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 1 5 1 5 5 - 6

Optimization Models for Rail Car Fleet Management represents the result of multi-year efforts to provide readers with insights into one of the most important areas of railway t… Read more

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Optimization Models for Rail Car Fleet Management represents the result of multi-year efforts to provide readers with insights into one of the most important areas of railway transport management. The book covers mathematical procedures for the effective and efficient utilization of railway freight cars, developed models for optimization methods, heterogeneity and partial substitutability of freight cars, research and development in rail freight car fleet management models, and the stochastic and dynamic nature of the supply, demand and traveling time of freight cars, among other topics.

1. Introduction1.1 Problem statement1.2 Main objectives1.3 Structure of the book

2. Review of the models for rail freight car fleet management2.1 Operational models2.1.1 Empty freight car inventory management problems2.1.2 Empty freight car distribution2.1.2.1 Deterministic approaches2.1.2.2 Stochastic approaches2.1.2.3 Hybrid approaches2.1.3 Freight car pooling concept2.1.4 Combined allocation of empty and loaded cars2.2 Tactical and strategic models for freight car management2.2.1 Service network design problem2.2.2 Demand estimation2.2.2.1 Models for production and attraction2.2.2.2 Distribution models2.2.2.3 Models for modal split2.2.2.4 Assignment models2.2.3 Rail freight car fleet sizing models

3 Centralized and decentralized Model for empty freight car scheduling3.1 Characteristics of decentralized managerial-control functions in the process of empty freight car allocation3.2 Centralized network model3.3 Solution method of triaxial transportation problem3.4 Decentralization of the main managerial functions in the empty car allocation process3.5 Decentralized terminal model of empty freight car allocation3.6 Validation of proposed model

4. Fuzzy multiobjective rail freight car fleet composition4.1 The best rail freight car fleet mix problem4.1.1 Classification of freight cars4.1.2 Utilization of freight cars according to their characteristics4.1.3 Proposed problem solution4.1.3.1 The selection of relevant criteria4.1.3.2 Analytic Hierarchy Process (AHP)4.1.3.3 Theoretical basics of AHP4.1.3.4 Mathematical basics of AHP4.1.3.5 Fuzzy extension of AHP method4.1.4 Fuzzy AHP method for the best rail freight car fleet mix problem4.2 The best rail freight car fleet size problem4.2.1 Theoretical foundations of the problem solution4.2.2 Fuzzy multi-objective linear programming4.2.3 Statement and solution of the problem

5. Fuzzy random model for rail freight car fleet management based on optimal control theory5.1 Fuzzy preliminaries5.1.1 Fuzzy sets5.1.2 Fuzzy numbers5.1.3 Triangular fuzzy matrices5.1.4 The main features of triangular fuzzy matrices5.1.5 Inverse triangular fuzzy matrices5.1.6 Defuzzification of triangular fuzzy numbers5.1.7 Fuzzy random variables5.2 Fuzzy stochastic model for rail freight car fleet sizing and allocation5.2.1 Model parameters5.2.2 Objective functional5.2.3 Problem constraints5.2.4 Fuzzy state vector estimation5.2.5 Proposed approach for solving the problem based on the fuzzy linear quadratic Gaussian regulator5.2.6 The components of weighting matrices A, B and L5.2.7 Choosing the components of the fuzzy weighting matrix5.3 Numerical experiments5.4 Comparative analysis of the results of the fuzzy random and random model

6. Stochastic model for heterogeneous rail freight car fleet management based on the model predictive control6.1 Discrete time MPC framework for rail freight car fleet sizing and allocation problem6.2 Design variables6.3 System performance measure and constraints6.4 State vector estimation6.5 Forecasting the state of rail freight cars by Arima-Kalman method6.5.1 Components of weighted matrices A, B and L6.5.2 The components of matrix6.6 MPC controller6.6.1 Optimization problem6.6.2 Detailed description of the MPC approach6.6.3 Numerical experiments

7. Distributed and decentralized approaches for rail freight car management7.1 Distributed model predictive rail freight car management7.1.1 Problem description7.1.2 Cooperative model predictive control for freight car flow planning7.2 Decentralized model predictive rail freight car management7.3 Numerical example

8. ConclusionsReferences

Milos Milenkovic

Milos Milenkovic is Assistant Professor at The Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia and Research Fellow at the MIT-Zaragoza International Logistics Program, Zaragoza, Spain. Dr. Milenkovic has a Ph.D. degree of Technical Sciences in the field of Traffic and Transportation with a focus on rail freight car scheduling and fleet sizing problems, Magisterial degree of Technical Sciences with a focus on train dispatching problems and M.Sc. degree based on railway related intelligent transportation systems from the Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia. Dr. Milenkovic´s main research areas are mathematical optimization, model predictive control theory, time series analysis, project management and engineering economy with a special focus on transport related applications. He was engaged as the member of editorial board of a number of scientific conferences and also as a reviewer of a number of prestigious peer-reviewed journals, like ”Transportation Research Part C”, ”Transportation Research Part E”, ”Applied Mathematical Modelling”, “International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems” and others. During his career Dr Milenkovic published more than fifty papers in journals as well as on scientific conferences. Dr. Milenkovic has also been employed for two years in Public Enterprise ”Serbian Railways” as a leading engineer for traffic organization and timetable construction.

Affiliations and expertise

Assistant Professor, The Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia and Research Fellow, MIT-Zaragoza International Logistics Program, Zaragoza, Spain

Nebojsa Bojovic

Nebojša Bojović is Full Professor and Dean at the Faculty of Transport and Traffic Engineering, University of Belgrade. Serbia. His professional expertise, research and teaching interests include Applications of Operations Research, Information Systems and Control Theory in Transportation Systems with particular emphasis on: Rail freight car fleet sizing, Railway vehicle routing and scheduling, Risk management, and Project management. He is author of 4 monographs, 2 chapters in international monographs, over 30 scientific publications bridge appeared in international journals, as well as over 70 papers presented at international and national conferences. His professional engagement include membership in Euro Working Group on Transportation, Euro Working Group on Multicriteria Decision Aiding, Academy of Engineering Sciences of Serbia, Board of Directors of the Serbian Tariffs Association, Yugoslav Society of Operational Research, Yugoslav Association for Project Management. He was a member of the Organizational and Scientific Committees at 5 international scientific conferences. He is also representative of the Faculty of Transport and Traffic Engineering within the international associations European Association for Research in Transportation (hEART) and EUropean Rail Research Network of Excellence (EURNEX). He is a reviewer in number of high-ranked international journals, such as: Transportation Research Part B, Transportation Research Part E, European Journal of Operational Research, Computational and Mathematical Organization Theory and other.

Affiliations and expertise

Faculty of Transport and Traffic Engineering, University of Belgrade, Serbia