http://servo.ad.wlu.edu/dokuwiki/ 2026-04-19T01:07:06+00:00 http://servo.ad.wlu.edu/dokuwiki/ http://servo.ad.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png text/html 2011-01-19T23:29:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter0?rev=1295479745&do=diff Chapter 0 The preface introduces us why analyzing algorithms are important. It provides examples within pure computer science domain, such as website design. The preface also talks about outside pure cs into why algorithm efficiency is important in real life application, such as staffing protocols for hospitals. No doubt, actual programming is important. But understanding the most innate scheme of codes is more crucial. Because it points out for us an outline along which we should add more deco… text/html 2011-01-19T23:28:19+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter1?rev=1295479699&do=diff Chapter 1 This chapter discusses one problem in details and introduces 5 types of problems of distinct complexities. Section 1: Stable Matching This section talks about the stable matching problem. It first introduces the problem and the associated history. Then a solution is given in details. Next, the solution algorithm is analyzed. Last, the book states some properties of the algorithm and gives out proofs.Most and the most core materials in this section are covered in class. Thus the rea… text/html 2011-01-27T01:09:03+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter2?rev=1296090543&do=diff Chapter 2 This chapter introduces us the basic mathematical tools needed for algorithm analysis. Section 1: Computational Tractability This section introduces several ways of defining “efficiency”. The first way is the literal meaning of “efficiency”-it runs quickly. The second way is defined through comparison: if an algorithm can be designed to run faster than the most basic “brute-force search” way, then it is efficiency. The third way is that if an algorithm can be run in linear time, th… text/html 2011-02-15T07:33:43+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter3?rev=1297755223&do=diff Chapter 3 This chapter introduces us the basic knowledge of graph. Section 1: Basic Definitions and Applications The section first introduces some basic concepts and notations of graph, such as vertex, edge, and orientation of graphs. Then several examples are illustrated: transportation networks that are tangible, though in practice directed, can be viewed as indirected graph, since the traffic normally comes both ways; Communication networks-basically just connecting computers together a… text/html 2011-03-02T04:59:18+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter4?rev=1299041958&do=diff Chapter 4 This chapter, as its descriptive title indicates, talks about greedy algorithm. The introduction of the chapter first points out the philosophy behind the different greedy algorithms: using a local decision to optimal small steps and constructing a overall optimal solution at the same time. Then the introduction summarizes the context of the chapter: listing out examples to let us get a feeling of why greedy algorithms are greedy. text/html 2011-03-14T00:52:38+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter5?rev=1300063958&do=diff Chapter 5 This chapter deals with the Divide and Conquer problems involving recurrence relations.This method can sometimes improve O(n^2) time to O(nlogn) time. Section 1: A First Recurrence: The Mergesort Algorithm This section introduces the first example in Divide and Conquer: mergesort. The idea of mergesort is to keep dividing a problem into two equal sizes, till the running time of dealing with the problem becomes constant, that is to T(2) text/html 2011-04-03T05:29:26+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter6?rev=1301808566&do=diff Chapter 6 Often, we face a situation where there is no natural greedy algorithm exist and the divide and conquer algorithm is not effective in terms of reducing algorithm, such as when we do not know “what is coming next”. Then we turn to Dynamic Programming, where we carefully play around with the algorithm such that it is close to brute-force search but systematically work to save running time. text/html 2011-04-04T05:39:11+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/chapter7?rev=1301895551&do=diff Chapter 7 Many problems can evolve from the Bipartite Matching problem, such as the perfect matching problem, the assigning-job-to-machine problem, and what we focus on this chapter-network flow problem. Section 1: The Maximum-Flow and the Ford-Fulkerson Algorithm text/html 2011-04-04T02:52:50+00:00 Anonymous (anonymous@undisclosed.example.com) http://servo.ad.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/wendy/home?rev=1301885570&do=diff Wendy's Journal * Chapter 0:Preface * Chapter 1: Introduction * Chapter 2: Algorithm Analysis * Chapter 3: Graphs * Chapter 4: Greedy Algorithms * Chapter 5: A First Recurrence: The Mergesort Algorithm * Chapter 6: Dynamic Programming * Chapter 7: Network Flow