A problem is NP-Hard if all other problems in NP can be polynomial-time-reducible, or mapped to it. It is at least as hard as the hardest problem in NP.
- Title Page
- Copyright and Credits
- Dedication
- Packt Upsell
- Contributors
- Acknowledgments
- Preface
- Python Objects, Types, and Expressions
- Python Data Types and Structures
- Technical requirements
- Built-in data types
- None type
- Numeric types
- Representation error
- Membership, identity, and logical operations
- Sequences
- Learning about tuples
- Beginning with dictionaries
- Sorting dictionaries
- Dictionaries for text analysis
- Sets
- Modules for data structures and algorithms
- Summary
- Principles of Algorithm Design
- Lists and Pointer Structures
- Stacks and Queues
- Trees
- Hashing and Symbol Tables
- Graphs and Other Algorithms
- Searching
- Sorting
- Selection Algorithms
- String Algorithms and Techniques
- Design Techniques and Strategies
- Implementations, Applications, and Tools
- Other Books You May Enjoy
NP-Hard
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