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小木虫论坛-学术科研互动平台 » 专业学科区 » 土木建筑 » 求助：Network Flows: Theory, Algorithms, and Applications
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yjb

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[交流] 求助：Network Flows: Theory, Algorithms, and Applications

现在我急需这本书，谁又这本书?
先谢谢了!
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yjb

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D.P. Bertsekas, Linear Network Optimization: Algorithms and Codes. MIT Press, 1991. Includes code for a variety of network algorithms.
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建议到    http://print.google.com上搜速一下
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yjb

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R.K. Ahuja, T.L. Magnanti and J.B. Orlin, Network Flows: Theory, Algorithms, and Applications. Prentice-Hall, 1993. A comprehensive recent survey of the topic.
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Network Flows: Theory, Algorithms, and Applications
Ravindra K. Ahuja, Thomas L. Magnanti, and James B. Orlin

BOOK CONTENTS



CHAPTER 1. INTRODUCTION
    1.1 Introduction
    1.2 Network Flow Problems
    1.3 Applications
    1.4 Summary
          Reference Notes
          Exercises

CHAPTER 2. PATHS, TREES AND CYCLES
    2.1 Introduction
    2.2 Notation and Definitions
    2.3 Network Representations
    2.4 Network Transformations
    2.5 Summary
          Reference Notes
          Exercises

CHAPTER 3. ALGORITHM DESIGN AND ANALYSIS
    3.1 Introduction
    3.2 Complexity Analysis
    3.3 Developing Polynomial-Time Algorithms
    3.4 Search Algorithms
    3.5 Flow Decomposition Algorithms
    3.6 Summary
          Reference Notes
          Exercises

CHAPTER 4. SHORTEST PATHS: LABEL SETTING ALGORITHMS
    4.1 Introduction
    4.2 Applications
    4.3 Tree of Shortest Paths
    4.4 Shortest Path Problems in Acyclic Networks
    4.5 Dijkstra’s Algorithm
    4.6 Dial’s Implementation
    4.7 Heap Implementations
    4.8 Radix Heap Implementation
    4.9 Summary
          Reference Notes
          Exercises

CHAPTER 5. SHORTEST PATHS: LABEL CORRECTING ALGORITHMS
    5.1 Introduction
    5.2 Optimality Conditions
    5.3 Generic Label Correcting Algorithms
    5.4 Special Implementations of the Modified Label Correcting Algorithm
    5.5 Detecting Negative Cycles
    5.6 All Pairs Shortest Path Problem
    5.7 Minimum Cost-to-Time Ratio Cycle Problem
    5.8 Summary
          Reference Notes
          Exercises

CHAPTER 6.  MAXIMUM FLOWS : BASIC IDEAS
    6.1 Introduction
    6.2 Applications
    6.3 Flows and Cuts
    6.4 Generic Augmenting Path Algorithm
    6.5 Labeling Algorithm and the Max-Flow Min-Cut Theorem
    6.6 Combinatorial Implications of the Max-Flow Min-Cut Theorem
    6.7 Flows with Lower Bounds
    6.8 Summary
          Reference Notes
          Exercises

CHAPTER 7.  MAXIMUM FLOWS : POLYNOMIAL ALGORITHMS
    7.1 Introduction
    7.2 Distance Labels
    7.3 Capacity Scaling Algorithm
    7.4 Shortest Augmenting Path Algorithm
    7.5 Distance Labels and Layered Networks
    7.6 Generic Preflow-Push Algorithm
    7.7 FIFO Preflow-Push Algorithm
    7.8 Highest Label Preflow-Push Algorithm
    7.9 Excess-Scaling Algorithm
    7.10 Summary
           Reference Notes
           Exercises

CHAPTR 8. MAXIMUM FLOWS : ADDITIONAL TOPICS
    8.1 Introduction
    8.2 Flows in Unit Capacity Networks
    8.3 Flows in Bipartite Networks
    8.4 Flows in Planar Undirected Networks
    8.5 Dynamic Tree Implementations
    8.6 Network Connectivity
    8.7 All pairs Minimum Cut Problem
    8.8 Summary
          Reference Notes
          Exercises

CHAPTER 9. MINIMUM COST FLOWS : BASIC ALGORITHMS
    9.1 Introduction
    9.2 Applications
    9.3 Optimality Conditions
    9.4 Minimum Cost Flow Duality
    9.5 Relating Optimal Flows to Optimal Node Potentials
    9.6 Cycle Canceling Algorithm and the Integrality Property
    9.7 Successive Shortest Path Algorithm
    9.8 Primal-Dual Algorithm
    9.9 Out-of-Kilter Algorithm
    9.10 Relaxation Algorithm
    9.11 Sensitivity Analysis
    9.12 Summary
           Reference Notes
           Exercises

CHAPTER 10. MINIMUM COST FLOWS : POLYNOMIAL ALGORITHMS
    10.1 Introduction
    10.2 Capacity Scaling Algorithm
    10.3 Cost Scaling Algorithm
    10.4 Double Scaling Algorithm
    10.5 Minimum Mean Cycle Canceling Algorithm
    10.6 Repeated Capacity Scaling Algorithm
    10.7 Enhanced Capacity Scaling Algorithm
    10.8 Summary
            Reference Notes
            Exercises

CHAPTER 11. MINIMUM COST FLOWS : NETWORK SIMPLEX ALGORITHMS
    11.1 Introduction
    11.2 Cycle Free and Spanning Tree Solutions
    11.3 Maintaining a Spanning Tree Structure
    11.4 Computing Node Potentials and Flows
    11.5 Network Simplex Algorithm
    11.6 Strongly Feasible Spanning Trees
    11.7 Network Simplex Algorithm for the Shortest Path Problem
    11.8 Network Simplex Algorithm for the Maximum Flow Problem
    11.9 Related Network Simplex Algorithms
    11.10 Sensitivity Analysis
    11.11 Relationship to Simplex Method
    11.12 Unimodularity Property
    11.13 Summary
              Reference Notes
              Exercises

CHAPTER 12. ASSIGNMENTS AND MATCHINGS
    12.1 Introduction
    12.2 Applications
    12.3 Bipartite Cardinality Matching Problem
    12.4 Bipartite Weighted Matching Problem
    12.5 Stable Marriage Problem
    12.6 Nonbipartite Cardinality Matching Problem
    12.7 Matchings and Paths
    12.8 Summary
            Reference Notes
            Exercises

CHAPTER 13. MINIMUM SPANNING TREES
    13.1 Introduction
    13.2 Applications
    13.3 Optimality Conditions
    13.4 Kruskal’s Algorithm
    13.5 Prim’s Algorithm
    13.6 Sollin’s Algorithm
    13.7 Minimum Spanning Trees and Matroids
    13.8 Minimum Spanning Trees and Linear Programming
    13.9 Summary
            Reference Notes
            Exercises

CHAPTER 14. CONVEX COST FLOWS
    14.1 Introduction
    14.2 Applications
    14.3 Transformations to a Minimum Cost Flow Problem
    14.4 Pseudopolynomial-Time Algorithms
    14.5 A Polynomial-Time Algorithm
    14.6 Summary
           Reference Notes
            Exercises

CHAPTER 15. GENERALIZED FLOWS
    15.1 Introduction
    15.2 Applications
    15.3 Augmented Forest Structures
    15.4 Determining Potentials and Flows for an Augmented Forest Structure
    15.5 Good Augmented Forests and Linear Programming Bases
    15.6 Generalized Network Simplex Algorithm
    15.7 Summary
            Reference Notes
            Exercises

CHAPTER 16. LAGRANGIAN RELAXATION AND NETWORK OPTIMIZATION
    16.1 Introduction
    16.2 Problem Relaxations and Branch and Bound
    16.3 Lagrangian Relaxation Technique
    16.4 Lagrangian Relaxation and Linear Programming
    16.5 Applications of Lagrangian Relaxation
    16.6 Summary
            References Notes
            Exercises

CHAPTER 17. MULTICOMMODITY FLOWS
    17.1 Introduction
    17.2 Applications
    17.3 Optimality Conditions
    17.4 Lagrangian Relaxation
    17.5 A Column Generation Procedure
    17.6 Dantzig-Wolfe Decomposition
    17.7 Resource-directive Decomposition
    17.8 Basis Partitioning
    17.9 Summary
            Reference Notes
            Exercises

CHAPTER 18. COMPUTATIONAL TESTING OF ALGORITHMS
    18.1 Introduction
    18.2 Representative Operation Counts
    18.3 Application to Network Simplex Algorithm
    18.4 Summary
            Reference Notes
            Exercises

CHAPTER 19. ADDITIONAL APPLICATIONS
    19.1 Introduction
    19.2 Maximum Weight Closure of a Graph
    19.3 Data Scaling
    19.4 Science Applications
    19.5 Project Management
    19.6 Dynamic Flows
    19.7 Arc Routing Problems
    19.8 Facility Layout and Location
    19.9 Production and Inventory Planning
    19.10 Summary
              Reference Notes
              Exercises

APPENDIX A. DATA STRUCTURES
    A.1 Introduction
    A.2 Elementary Data Structures
    A.3 d-Heaps
    A.4 Fibonacci Heaps
           Reference Notes

APPENDIX B. NP-COMPLETENESS
    B.1 Introduction
    B.2 Problem Reductions and Transformations
    B.3 The Problem Classes P, NP, NP-Complete and NP-Hard
    B.4 Proving NP-Completeness Results
           Reference Notes

APPENDIX C. LINEAR PROGRAMMING
    C.1 Introduction
    C.2 Graphical Solution Procedure
    C.3 Basic Feasible Solutions
    C.4 The Simplex Method
    C.5 Bounded Variable Simplex Method
    C.6 Duality Theory
          Reference Notes
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