MODELING AND SIMULATION OF LOGISTICS FLOWS : theory and fundamentals

Content: Cover 
 Title Page
 Copyright
 Contents
 Foreword
 About This Book
 Intended public
 Organization and contents of the book
 Conventions
 Vocabulary and definition
 Acknowledgments
 Introduction
 I.1. What is logistics?
 I.2. History
 I.3. New tools and new technologies
 1. Operational Research
 1.1. A history
 1.2. Fields of application, principles and concepts
 1.2.1. Identification
 1.2.2. Modeling
 1.2.3. Solution
 1.2.4. Validation
 1.2.5. Implementation
 1.2.6. Improvement
 1.3. Basic models
 1.4. The future of OR
 2. Elements of Graph Theory
 2.1. Graphs and representations. 2.2. Undirected graph2.2.1. Multigraph
 2.2.2. Planar and non-planar graph
 2.2.3. Connected and unconnected graph
 2.2.4. Complete graph
 2.2.5. Bipartite graph
 2.2.6. Partial graph, subgraph, clique and stable
 2.2.7. Degree of a vertex and a graph
 2.2.8. Chain and cycle in a graph
 2.2.9. Level of connectivity (or beta index)
 2.2.10. Eulerian graph
 2.2.11. Hamiltonian graph
 2.2.12. Planar graph
 2.2.13. Isthmus
 2.2.14. Tree and forest
 2.2.15. Arborescence
 2.2.16. Ordered arborescence
 2.3. Directed graph or digraph
 2.3.1. Path and circuit in a digraph. 2.3.2. Absence of circuit in a digraph2.3.3. Adjacency matrix
 2.3.4. Valued graph matrix
 2.4. Graphs for logistics
 3. Optimal Paths
 3.1. Basic concepts
 3.2. Dijkstra\'s algorithm
 3.2.1. An example of calculating minimal paths
 3.2.2. Interpreting the results of the calculations
 3.3. Floyd-Warshall\'s algorithm
 3.3.1. Creating the starting matrices (initialization of the algorithm)
 3.3.2. Filling the matrices for the following repetitions
 3.3.3. An example of calculating minimal paths
 3.3.4. Interpreting the results
 3.4. Bellman-Ford\'s algorithm
 3.4.1. Initialization. 3.4.2. The next repetitions with relaxation3.4.3. An example of calculation
 3.4.4. Interpreting the results
 3.5. Bellman-Ford\'s algorithm with a negative circuit
 3.5.1. Example
 3.6. Exercises
 3.6.1. Exercise 1: Optimizing journey time
 3.6.2. Exercise 2: A directed graph with negative cost side
 3.6.3. Exercise 3: Routing data packets
 3.6.4. Solutions to exercise 1
 3.6.5. Solutions to exercise 2
 3.6.6. Solutions to exercise 3
 4. Dynamic Programming
 4.1. The principles of dynamic programming
 4.2. Formulating the problem
 4.2.1. Example 1: The pyramid of numbers. 4.2.2. Example 2: The Fibonacci sequence4.2.3. Example 3: The knapsack
 4.3. Stochastic process
 4.4. Markov chains
 4.4.1. Property of Markov chains
 4.4.2. Classes and states of a chain
 4.4.3. Matrix and graph
 4.4.4. Applying Markov chains
 4.5. Exercises
 4.5.1. Exercise 1: Levenshtein distance
 4.5.2. Exercise 2
 4.5.3. Exercise 3: Ehrenfest model
 4.5.4. Solutions to exercise 1
 4.5.5. Solutions to exercise 2
 4.5.6. Solutions to exercise 3
 5. Scheduling with PERT and MPM
 5.1. Fundamental concepts
 5.2. Critical path method
 5.3. Precedence diagram.