Data Structures and Algorithms in Java
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  • Preface
    • Syllabus
    • Schedule
  • 0. Getting Started
    • 0.1. Environment Setup
    • 0.2. Quiz
  • 1. Java Essentials
    • 1.1. Abstraction
    • 1.2. Implementation
    • 1.3. Unit Testing
    • 1.4. Quiz
  • 2. Priority Queues
    • 2.1. Simple Priority Queues
    • 2.2. Binary Heap
    • 2.3. Unit Testing
    • 2.4. Benchmarking
    • 2.5. Quiz
  • 3. Sorting Algorithms
    • 3.1. Abstraction
    • 3.2. Comparison-based Sort
    • 3.3. Divide & Conquer Sort
    • 3.4. Distribution-based Sort
    • 3.5. Quiz
    • 3.6. Homework
  • 4. Binary Search Trees
    • 4.1. Binary Search Trees
    • 4.2. Balanced BST
    • 4.2. AVL Trees
    • 4.3. Red-Black Trees
    • 4.4. Quiz
  • 5. Tries
    • 5.1. Concept
    • 5.2. Implementation
    • 5.3. Quiz
    • 5.4. Homework
  • 6. Disjoint Sets
    • 6.1. Concept
    • 6.2. Implementation
    • 6.3. Quiz
  • 7. Graphs
    • 7.1. Implementation
    • 7.2. Cycle Detection
    • 7.3. Topological Sorting
    • 7.4. Quiz
  • 8. Minimum Spanning Trees
    • 8.1. Abstraction
    • 8.2. Prim's Algorithm
    • 8.3. Kruskal’s Algorithm
    • 8.4. Edmonds' Algorithm
    • 8.5. Quiz
    • 8.6. Homework
  • 9. Network Flow
    • 9.1. Flow Network
    • 9.2. Ford-Fulkerson Algorithm
    • 9.3. Simplex Algorithm
    • 9.3. Quiz
  • 10. Dynamic Programming
    • 10.1. Fibonacci Sequence
    • 10.2. Tower of Hanoi
    • 10.3. Longest Common Subsequence
    • 10.4. Quiz
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  • Max-Flow Min-Cut Theorem
  • Simplex: Prime
  • Simplex: Dual

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  1. 9. Network Flow

9.3. Simplex Algorithm

Previous9.2. Ford-Fulkerson AlgorithmNext9.3. Quiz

Last updated 4 years ago

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Max-Flow Min-Cut Theorem

Let SSS - TTT cut be a set of edges whose removal disconnects any path between SSS and TTT:

What is the relationship between max-flow and min-cut?

Simplex: Prime

Maximize p = 0x1 + x2 + 0x3 + x4 subject to
x1 <= 4
x2 <= 2
x3 <= 3
x4 <= 2
x2 - x1 <= 0
x4 - x3 <= 0

Maximize p = 0x1 + 0x2 + 0x3 + 0x4 + 0x5 + 0x6 + x7 + x8  subject to
x1 <= 4
x2 <= 2
x3 <= 3
x4 <= 2
x5 <= 3
x6 <= 1
x7 <= 2
x8 <= 4
x3 - x1 <= 0
x4 + x5 - x2 - x6 <= 0
x6 + x7 - x3 - x4 <= 0
x8 - x5 <= 0

Simplex: Dual

Minimize p = 4x1 + 2x2 + 3x3 + 2x4 + 0y1 + 0y3  subject to
x1 + y1 >= 1
x3 + y3 >= 1
x2 - y1 >= 0
x4 - y3 >= 0

Minimize p = 4x1 + 2x2 + 3x3 + 2x4 +
3x5 + x6 + 2x7 + 4x8 + 0y1 + 0y2 + 0y3 + 0y4  subject to
x1 + y1 >= 1
x2 + y2 >= 1
x3 - y1 + y3 >= 0
x4 - y2 + y3 >= 0
x5 - y2 + y4 >= 0
x6 - y3 + y2 >= 0
x7 - y3 >= 0
x8 - y4 >= 0