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Algorithms: Design Techniques and Analysis (Lecture Notes Series on Computing), by M H Alsuwaiyel
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Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.Algorithms: Design Techniques and Analysis advocates the study of algorithm design by presenting the most useful techniques and illustrating them with numerous examples emphasizing on design techniques in problem solving rather than algorithms topics like searching and sorting. Algorithmic analysis in connection with example algorithms are explored in detail. Each technique or strategy is covered in its own chapter through numerous examples of problems and their algorithms.Readers will be equipped with problem solving tools needed in advanced courses or research in science and engineering.
- Published on: 2016-04-28
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.30" w x 6.20" l, .0 pounds
- Binding: Hardcover
- 572 pages
Most helpful customer reviews
8 of 8 people found the following review helpful.
An excellent book on algorithm analysis
By Dr. Marina Gavrilova
The book represents a well written, consistent and easy to follow view on the area of algorithm analysis. It gives an excellent overview of various mathematical and computer science areas, including but not limited to combinatorial geometry, NP-problems, complexity theory, graph theory, algorithm analysis, dynamic programming and even computational geometry.
Most of the chapters are intended for a senior level undergraduate and graduate student, but some (such as part 4 devoted to complexity problems) are more suitable for "mature" audience and require some preliminary knowledge in the area.
I found chapters on sorting, data structures, recursion and functional programming well written and structured, and examples to be practical as well as informative.
Sections on amortized analysis, randomized algorithms, approximation algorithms and iteration improvement deal with current directions in the algorithmic research and provide an excellent overview of the "state-of-the-art" in these areas. I also enjoyed reading through the section on greedy algorithms (shortest path and minimum spanning tree problems).
Section on computational complexity and analysis of the relationship between complexity classes seems to be a bit complicated, those who are interested in this area should probably do some preliminary reading.
The last section on computational geometry (my area of expertise) and applications of Voronoi diagrams could be extended, but even in the current state it givs a pretty good idea of what computational geometry is all about.
Overall, I give to this book a "5 star" review and recommend it for anyone who is seriously interested in learning exactly how algorithm design and analysis work. I thoroughly enjoyed reading this book and can only wish that author would write more books like that in the future!
1 of 1 people found the following review helpful.
Overpriced, uninspired.
By ZeroCool2u
I've used this book for my undergraduate algorithms class and I must say, I find it incredibly frustrating. I will say it is not all bad. The book does a decent job of providing grounded explanations, but fails miserably in numerous ways. Just a few of my more basic issues with the book are as follows.
1. A multitude of grammatical flaws. The book was, by definition, poorly edited. This is unacceptable when considering the outlandish price.
2. There are absolutely no solutions. I don't believe all or even most solutions need be present, but this is a fairly common practice that is completely ignored by this book and only works to hinder students confidence in whether or not they've successful absorbed and digested the material. The book is also not commonly used, so there is little to no discussion online of common issues experienced with the book.
3. The book lacks some of the more detailed mathematical explanations that some students might be looking for. This may only be an issue for a small subset of students, but is certainly worth noting, when such explanations are easily found in other, more effectives texts.
4. All counting in the book starts at 1, not 0. This is subjective and in fact most algorithms textbooks do this, but I still personally find it annoying when implementing algorithms based on the books pseudocode, the format of which I am also not a fan. If you find yourself in the same boat, consider reading this threads explanation on why many textbooks do this. [...]
As you can see others have had success with this book and it is certainly possible to learn from this book, but I thoroughly believe there are better, far more effective books for teaching a class on Algorithms. Personally, I would suggest either The Algorithm Design Manual or Introduction to Algorithms, 3rd Edition (MIT Press). Neither books are without their flaws, but both are clearly stronger choices than this. Especially considering they are significantly cheaper and there is far more information available on the specifics covered in either of them.
1 of 1 people found the following review helpful.
Better than the other books.. but not perfect
By nee
This is a great book overall, but I give it 4 stars as it lacks the mathematical explanations that I personally was looking for. I am graduate student in Computer Science and a E-Commerce Consultant by profession. This book is more detailed than the Sedweick (I can't spell his name) in the sense that it has some more of a mathematical approach. It lacks the level of explanation that the Sedweick book provided. It has some math, but overlooks some steps thus targeting someone with a pretty solid math background, not someone with sophomore level undergraduate math background.
Overall.. if you're a student taking an algorithms or advanced algorithms class (especially a graduate class), you might want to invest in this book.
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