一、課程說明(Course Desc<x>ription)
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<br>Computer algorithms specify unambiguous steps to solve specific problems. The efficiency of these 
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<br>algorithms can make huge impacts on the execution time or the memory requirement for solving large size 
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<br>problems. In this course, how to analyze an algorithm is first introduced. Then some common approaches to 
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<br>develop algorithms are described. That includes divide and conquer, greedy algorithms, dynamic 
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<br>programming, branch and bound, etc. Finally, some known hard problems that would take very long time to 
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<br>find the best solution are presented. If a problem falls into this category, known as NP-complete problems, 
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<br>then one should not try to find the exact solution, instead, a sub-optimal solution should be sought for. 
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<br>Extensive research on writing effective algorithms to solve practical problems have been carried out in the 
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<br>20'th century, this course covers some of the basic ones to enable students to develop algorithmic skills 
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<br>such that they can solve practical problems in the future.
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<br>二、指定用書(Text Books)
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<br>E. Horowitz, S. Sahni, and S. Rajasekeran, Computer Algorithms, 2nd Edition, Silicon Press, 2008.
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<br>三、參考書籍(References)
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<br>T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein, Introduction to Algorithms, 3rd Edition, The MIT Press, 
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<br>2009.
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<br>四、教學方式(Teaching Method)
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<br>Lecture and discussion.
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<br>五、教學進度(Syllabus)
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<br>1. Introduction
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<br>2. Program performance analysis
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<br>3. Divide and conquer
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<br>4. The greedy method
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<br>5. Dynamic programming
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<br>6. Traversal and search
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<br>7. Backtracking
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<br>8. Branch and bound
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<br>9. Lower bound theory
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<br>10. NP-hard and NP-complete problems
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<br>六、成績考核(Evaluation)
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<br>Homework: 50%
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<br>Midterm exam and quizzes : 30%
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<br>Final exam: 20%
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<br>七、可連結之網頁位址
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<br>To be provided later.