دانلود کتاب Practical Python AI Projects: Mathematical Models of Optimization Problems with Google OR-Tools

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Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Chapter 1: Introduction
1.1 What Is This Book About?
1.2 Features of the Text
1.2.1 Running the Models
1.2.2 A Note on Notation
1.3 Getting Our Feet Wet: Amphibian Coexistence
Chapter 2: Linear Continuous Models
2.1 Mixing
2.1.1 Constructing a Model
2.1.2 Variations
2.1.3 Structure of the Problems Under Consideration
2.2 Blending
2.2.1 Constructing a Model
2.2.2 Variations
2.3 Project Management
2.3.1 Constructing a Model
2.3.2 Variations
2.3.2.1 Minimax Problems
2.3.2.2 Absolute Value Problems
2.4 Multi-Stage Models
2.4.1 Problem Instance
2.4.2 Constructing a Model
2.4.2.1 Decision variables
2.4.2.2 Constraints
2.4.2.3 Objective Function
2.4.2.4 Executable Model
2.4.3 Variations
2.5 Pattern Classification
2.5.1 Constructing a Model
2.5.2 Executable Model
2.5.2.1 Variations
Chapter 3: Hidden Linear Continuous Models
3.1 Piecewise Linear
3.1.1 Constructing a Model
3.1.1.1 Constraints
3.1.1.2 Objective
3.1.1.3 Executable Model
3.1.2 Variations
3.1.2.1 Non-Linear Function Minimization via Linear Approximations
3.1.2.2 Non-Convex Piecewise Linear
3.2 Curve Fitting
3.2.1 Constructing a Model
3.2.1.1 Objective Function
3.2.1.2 Constraints
3.2.1.3 Executable Model
3.2.2 Variations
3.3 Pattern Classification Revisited
3.3.1 Executable Model
Chapter 4: Linear Network Models
4.1 Maximum Flow
4.1.1 Constructing a Model
4.1.2 Decision Variables
4.1.2.1 Objective
4.1.2.2 Constraints
4.1.2.3 Executable Model
4.1.3 Variations
4.2 Minimum Cost Flow
4.2.1 Constructing a Model
4.2.1.1 Decision Variables
4.2.1.2 Objective
4.2.1.3 Constraints
4.2.1.4 Executable Model
4.2.2 Variations
4.3 Transshipment
4.3.1 Constructing a Model
4.3.1.1 Objective
4.3.1.2 Constraints
4.3.1.3 Executable Model
4.3.2 Variations
4.4 Shortest Paths
4.4.1 Constructing a Model
4.4.2 Alternate Algorithms
4.4.3 Variations
Chapter 5: Classic Discrete Models
5.1 Minimum Set Cover
5.1.1 Constructing a Model
5.1.1.1 Decision Variables
5.1.1.2 Objective
5.1.1.3 Constraints
5.1.1.4 Executable Model
5.1.2 Variations
5.2 Set Packing
5.2.1 Constructing a Model
5.2.1.1 Decision Variables
5.2.1.2 Objective
5.2.1.3 Constraints
5.2.1.4 Executable Model
5.2.2 Variations
5.3 Bin Packing
5.3.1 Constructing a Model
5.3.1.1 Decision Variables
5.3.1.2 Constraints
5.3.1.3 Objective
5.3.1.4 Executable Model
5.3.1.5 Variations
5.4 TSP
5.4.1 Constructing a Model
5.4.1.1 Decision Variables
5.4.1.2 Objective
5.4.1.3 Constraints
5.4.1.4 Executable Model
5.4.2 Variations
Chapter 6: Classic Mixed Models
6.1 Facility Location
6.1.1 Constructing a Model
6.1.1.1 Decision Variables
6.1.1.2 Objective
6.1.1.3 Constraints
6.1.1.4 Executable Model
6.1.2 Variations
6.2 Multi-Commodity Flow
6.2.1 Constructing a Model
6.2.1.1 Decision Variables
6.2.1.2 Objective
6.2.1.3 Constraints
6.2.1.4 Executable Model
6.2.2 Variations
6.2.2.1 All-Pairs Shortest Paths (Revisited)
6.2.3 Instances
6.3 Staffing Level
6.3.1 Constructing a Model
6.3.1.1 Decision Variables
6.3.1.2 Objective
6.3.1.3 Constraints
6.3.1.4 Executable Model
6.3.2 Variations
6.4 Job Shop Scheduling
6.4.1 Constructing a Model
6.4.1.1 Executable Model
Chapter 7: Advanced Techniques
7.1 Cutting Stock
7.1.1 Constructing a Model
7.1.1.1 Decision Variables
7.1.1.2 Objective
7.1.1.3 Constraints
7.1.1.4 Executable Model
7.1.2 Pre-Allocate Cutting Patterns
7.2 Non-Convex Trickery
7.2.1 Selecting k Variables Out of n to Be Non-Zero
7.2.2 Selecting k Adjacent Variables Out of n to Be Non-Zero
7.2.3 Selecting k Constraints Out of n
7.2.4 Maximax and Minimin
7.3 Staff Scheduling
7.3.1 Constructing a Model
7.3.1.1 Decision Variables
7.3.1.2 Constraints
7.3.1.3 Objective
7.3.1.4 Executable Model
7.3.2 Variations
7.4 Sports Timetabling
7.4.1 Constructing a Model
7.4.1.1 Decision Variables
7.4.1.2 Constraints
7.4.1.3 Objective Function
7.4.1.4 Executable Model
7.4.2 Variations
7.5 Puzzles
7.5.1 Pseudo-Chess Problems
7.5.2 Sudoku
7.5.3 Send More Money!
7.5.4 Ladies and Tigers
7.6 Quick Reference for OR-Tools MPSolver in Python
Index