PPT-CS38 Introduction to Algorithms

Author : briana-ranney | Published Date : 2020-04-08

Lecture 18 May 29 2014 May 29 2014 1 CS38 Lecture 18 May 29 2014 CS38 Lecture 18 2 Outline coping with intractibility approximation algorithms set cover TSP center

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CS38 Introduction to Algorithms: Transcript

Lecture 18 May 29 2014 May 29 2014 1 CS38 Lecture 18 May 29 2014 CS38 Lecture 18 2 Outline coping with intractibility approximation algorithms set cover TSP center selection randomness in algorithms. . NP-Complete. CSE 680. Prof. Roger Crawfis. Polynomial Time. Most (but not all) of the algorithms we have studied so far are easy, in that they can be solved in polynomial time, be it linear, quadratic, cubic, etc.. 1. Brute Force. A straightforward approach, usually based . directly. on the problem’s . statement and . definitions. . of the concepts involved. Examples – based directly on definitions:. Computing . &. Miriam . Leeser. Dana Brooks. mel@coe.neu.edu brooks@ece.neu.edu. 1. This . work . is supported by: . NSF . CenSSIS. - The Center for Subsurface Sensing and Imaging. 1. Brute Force. A straightforward approach, usually based . directly. on the problem’s . statement and . definitions. . of the concepts involved. Examples – based directly on definitions:. Computing . CS16: Introduction to Algorithms and Data Structures. Tu. /. Th. 10:30-11:50. Salomon DECI. Seny. Kamara. 1. Thursday, January . 26, 2017. What is 16 About?. Thursday, January 28, 2016. 2. Algorithms. Problem - a well defined task.. Sort a list of numbers.. Find a particular item in a list.. Find a winning chess move.. Algorithms. A series of precise steps, known to stop eventually, that solve a problem.. Lecture 17. May 27, . 2014. May 27, 2014. 1. CS38 Lecture 17. May 27, 2014. CS38 Lecture 17. 2. Outline. coping with . intractibility. NP-completeness. special cases. fixed parameter complexity. approximation algorithms. Programming - Purpose, structure and the outline of a program.. An overview – programming is: . analysis of a scenario/problem. defining a specification. identifying input, process and output testing/debugging.. 1. Brute Force. A straightforward approach, usually based . directly. on the problem’s . statement and . definitions. . of the concepts involved. Examples – based directly on definitions:. Computing . Practical: Starting out in Python. Teaching Computing to KS3. Course outline. Week No. Understanding computers. (5:00 – 6:00). Developing programming skills. (6:00 – 7:00). 23rd January. Algorithms. 1. Brute Force. A straightforward approach, usually based . directly. on the problem’s . statement and . definitions. . of the concepts involved. Examples – based directly on definitions:. Computing . 1. Decrease-and-Conquer. Reduce . original problem . instance to . smaller . instance . of the same problem. Solve smaller . instance. Extend solution . of smaller . instance . to obtain solution to original instance. 10 Bat Algorithms Xin-She Yang, Nature-Inspired Optimization Algorithms, Elsevier, 2014 The bat algorithm (BA) is a bio-inspired algorithm developed by Xin-She Yang in 2010. 10.1 Echolocation of Bats Introduction to Algorithms: Greedy Algorithms (and Graphs) Graphs ( R eview ) Definition . A directed graph ( digrap h ) G = ( V , E ) is an ordered pair consisting of a set V

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