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What Is Heuristic
In the fields of mathematical optimization and computer science, a heuristic is a strategy that is designed to solve a problem more rapidly in situations where traditional approaches are either too slow for finding an approximation answer or fail to find any accurate solution. In order to accomplish this, we must sacrifice optimality, completeness, accuracy, or precision in exchange for speed. It is possible to look at it as a short cut in some respects.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Heuristics in Computer Science
Chapter 2: Greedy Algorithm
Chapter 3: Divide and Conquer Algorithm
Chapter 4: Dynamic Programming
Chapter 5: Branch and Bound
Chapter 6: Backtracking
Chapter 7: A* Search Algorithm
Chapter 8: Simulated Annealing
Chapter 9: Genetic Algorithm
Chapter 10: Swarm Intelligence
(II) Answering the public top questions about heuristic.
(III) Real world examples for the usage of heuristic in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of heuristic' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of heuristic.
In the fields of mathematical optimization and computer science, a heuristic is a strategy that is designed to solve a problem more rapidly in situations where traditional approaches are either too slow for finding an approximation answer or fail to find any accurate solution. In order to accomplish this, we must sacrifice optimality, completeness, accuracy, or precision in exchange for speed. It is possible to look at it as a short cut in some respects.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Heuristics in Computer Science
Chapter 2: Greedy Algorithm
Chapter 3: Divide and Conquer Algorithm
Chapter 4: Dynamic Programming
Chapter 5: Branch and Bound
Chapter 6: Backtracking
Chapter 7: A* Search Algorithm
Chapter 8: Simulated Annealing
Chapter 9: Genetic Algorithm
Chapter 10: Swarm Intelligence
(II) Answering the public top questions about heuristic.
(III) Real world examples for the usage of heuristic in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of heuristic' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of heuristic.
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