http://cswiki.wlu.edu/dokuwiki/ 2026-04-29T11:42:35+00:00 http://cswiki.wlu.edu/dokuwiki/ http://cswiki.wlu.edu/dokuwiki/lib/exe/fetch.php/wiki/dokuwiki-128.png text/html 2011-01-19T04:11:41+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter1?rev=1295410301&do=diff This chapter introduces the stable matching problem created by David Gale and Lloyd Shapley. We discussed this problem in class at great length and this chapter of the book covers this problem at even greater length for better or for worse. As far as readability is concerned, this chapter is substantially less readable and therefore I would give it a 5/10. This chapter takes a hit on readability because we covered it so well in class that I felt like I wasn't receiving much more information out … text/html 2011-01-19T04:22:16+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter2?rev=1295410936&do=diff This section goes into great detail about defining efficiency and the bounds of a particular algorithm. The sections I read for this assignment (2.1 and 2.2) begin with a very broad definition of efficiency: “An algorithm is efficient if, when implemented, it runs quickly on real input instances. text/html 2011-01-26T03:02:36+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter2_continued?rev=1296010956&do=diff Chapter 2 2.3: Implementing the Stable Matching Algorithm Using Lists and Arrays *Arrays are simple to implement *Constant time retrieval of the ith element in the list *O(n) time to find out if an element is equal to another element in the list text/html 2011-02-02T04:32:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter3?rev=1296621141&do=diff Chapter 3 3.1: Basic Definitions and Applications *A graph is a way of encoding pairwise relationships among a set of objects *Has a set of nodes and a set of edges connecting these nodes *Directed and Undirected graphs * Directed graphs have direction in there edges whereas undirected graphs do not text/html 2011-03-01T22:13:01+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter4?rev=1299017581&do=diff Chapter 4 4.1: Interval Scheduling: The Greedy Algorithm Stays Ahead * A greedy algorithm is the optimum algorithm for a given problem * Starts with a simple rule then continues using that rule to solve the rest of the equation. * In this particular problem the greedy algorithm is the algorithm which produces the fewest conflicts between intervals. text/html 2011-03-14T20:31:03+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter5?rev=1300134663&do=diff Chapter 5 5.1: A First Recurrence: The Mergesort Algorithm * Mergesort is a great example of divide and conquer. * To quote Professor Stough: “Sorting is hard, so don't do it. Just merge” * From the book: * Divide the input into two pieces of equal size; solve the two subproblems on these pieces separately by recursion; and then combine the two results into an overall solution, spending only linear time for the initial division and final recombining. text/html 2011-04-05T23:24:28+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter6?rev=1302045868&do=diff Chapter 6 6.1: Weighted Interval Scheduling: A Recursive Procedure * More general version of the greedy algorithms we worked on before. * Dynamic programming solution: a recurrence equation that expresses the optimal solution (or its value) in terms of the optimal solutions to smaller sub-problems text/html 2011-04-05T23:51:14+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/chapter7?rev=1302047474&do=diff Chapter 7 7.1: The Maximum-Flow Problem and the Ford-Fulkerson Algorithm * Transportation networks - networks where the edges carry traffic and the nodes act as switches passing traffic between edges * Source nodes generate traffic * Sink nodes absorb traffic text/html 2011-04-05T23:25:10+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/home?rev=1302045910&do=diff Andrew's Journal Preface Chapter 1: Introduction Chapter 2: Basics of Algorithm Analysis Chapter 2(continued): Basics of Algorithm Analysis Chapter 3: Graphs Chapter 4: Greedy Algorithms Chapter 5: Divide and Conquer Chapter 6:Dynamic Programming Chapter 7:Network Flow text/html 2011-01-19T04:08:19+00:00 Anonymous (anonymous@undisclosed.example.com) http://cswiki.wlu.edu/dokuwiki/doku.php/courses/cs211/winter2011/journals/andrew/preface?rev=1295410099&do=diff The preface was a very brief summary of what's to come in the textbook. It was a very brief reading assignment and covered no actual material. That being said, it was very readable (probably because it did not introduce any new material) and I'll give it a 9/10. The one sentence that struck me while reading this chapter was the notion that