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190914s2020 ne ob 001 0 eng d |
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|a 9780128151556
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|a 0128151552
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|z 9780128151549
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|a TF470
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|a 625.2/4
|2 23
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|a Milenkovi�c, Milo�s.
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|a Optimization Models for Rail Car Fleet Management /
|c Milos Milenkovic, Nebojsa Bojovic.
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|a Amsterdam :
|b Elsevier,
|c 2020.
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300 |
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|a 1 online resource (286 pages)
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336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Print version record.
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|a Front Cover; Optimization Models for Rail Car Fleet Management; Copyright; Contents; Biographies; Acknowledgments; Executive summary; Chapter 1: Introduction; 1.1. Problem statement; 1.2. Main objectives; 1.3. Structure of the book; Chapter 2: Review of the models for rail freight car fleet management; 2.1. Operational models; 2.1.1. Empty freight car inventory management problems; 2.1.2. Empty freight car distribution; 2.1.2.1. Deterministic approaches; 2.1.2.2. Stochastic approaches; 2.1.2.3. Hybrid approaches; 2.1.3. Freight car pooling concept
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|a 2.1.4. Combined allocation of empty and loaded cars2.2. Tactical and strategic models for freight car management; 2.2.1. Service network design problem; 2.2.2. Demand estimation; 2.2.2.1. Models for production and attraction; 2.2.2.2. Distribution models; 2.2.2.3. Models for modal split; 2.2.2.4. Assignment models; 2.2.3. Rail freight car fleet sizing models; Chapter 3: Centralized and decentralized model for empty freight car scheduling; 3.1. Characteristics of decentralized managerial-control functions in the process of empty freight car allocation; 3.2. Centralized network model
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|a 3.3. Solution method of triaxial transportation problem3.3.1. Basic solution; 3.3.2. Feasible solution; 3.3.3. Final solution; 3.3.4. Problem of degeneration; 3.4. Decentralization of the main managerial functions in the empty car allocation process; 3.5. Decentralized terminal model of empty freight car allocation; 3.6. Validation of the proposed model; Chapter 4: Fuzzy multiobjective rail freight car fleet composition; 4.1. The best rail freight car fleet mix problem; 4.1.1. Classification of freight cars; 4.1.2. Utilization of freight cars according to their characteristics
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|a 4.1.3. Proposed problem solution4.1.3.1. The selection of relevant criteria; 4.1.3.2. Analytic Hierarchy Process; 4.1.3.3. Theoretical basics of AHP; 4.1.3.4. Mathematical basics of AHP; 4.1.3.5. Fuzzy extension of AHP method; 4.1.4. Fuzzy AHP method for the best rail freight car fleet mix problem; 4.2. The best rail freight car fleet size problem; 4.2.1. Theoretical foundations of the problem solution; 4.2.2. Fuzzy multiobjective linear programming; 4.2.3. Statement and solution of the problem
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|a Chapter 5: Fuzzy random model for rail freight car fleet management based on optimal control theory5.1. Fuzzy preliminaries; 5.1.1. Fuzzy sets; 5.1.2. Fuzzy numbers; 5.1.3. Triangular fuzzy matrices; 5.1.4. The main features of triangular fuzzy matrices; 5.1.5. Inverse triangular fuzzy matrices; 5.1.5.1. Necessary and sufficient conditions for the invertibility of fuzzy matrices; 5.1.5.2. Application of Rohn's scheme for determining of the inverse fuzzy matrix; 5.1.6. Defuzzification of triangular fuzzy numbers; 5.1.7. Fuzzy random variables
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500 |
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|a 5.2. Fuzzy stochastic model for rail freight car fleet sizing and allocation
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504 |
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|a Includes bibliographical references and index.
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650 |
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|a Freight cars.
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650 |
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|a Railroads
|x Management.
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650 |
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6 |
|a Wagons de marchandises.
|0 (CaQQLa)201-0019499
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650 |
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6 |
|a Transports ferroviaires
|x Gestion.
|0 (CaQQLa)201-0033339
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650 |
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|a freight cars.
|2 aat
|0 (CStmoGRI)aat300212993
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650 |
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|a Freight cars
|2 fast
|0 (OCoLC)fst01432139
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650 |
|
7 |
|a Railroads
|x Management
|2 fast
|0 (OCoLC)fst01089045
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700 |
1 |
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|a Bojovi�c, Neboj�sa.
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776 |
0 |
8 |
|i Print version:
|a Milenkovic, Milos.
|t Optimization Models for Rail Car Fleet Management.
|d San Diego : Elsevier, �2019
|z 9780128151549
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856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128151549
|z Texto completo
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