Assignment 2: Due Week 11, Friday

Slides:



Advertisements
Similar presentations
COMP 482: Design and Analysis of Algorithms
Advertisements

1 Chapter 4 Greedy Algorithms Slides by Kevin Wayne. Copyright © 2005 Pearson-Addison Wesley. All rights reserved.
MCA 301: Design and Analysis of Algorithms
Instructor Neelima Gupta Table of Contents Greedy Algorithms.
Chapter 4 The Greedy Approach. Minimum Spanning Tree A tree is an acyclic, connected, undirected graph. A spanning tree for a given graph G=, where E.
Approaches to Problem Solving greedy algorithms dynamic programming backtracking divide-and-conquer.
Approaches to Problem Solving greedy algorithms dynamic programming backtracking divide-and-conquer.
1 IOE/MFG 543 Chapter 3: Single machine models (Sections 3.1 and 3.2)
1 Pseudo-polynomial time algorithm (The concept and the terminology are important) Partition Problem: Input: Finite set A=(a 1, a 2, …, a n } and a size.
Lecture 37 CSE 331 Nov 4, Homework stuff (Last!) HW 10 at the end of the lecture Solutions to HW 9 on Monday Graded HW 9 on.
1. 2 Weighted interval scheduling for a lazy man Input: the same as weighted interval scheduling. Goal: find a set of compatible jobs such that for any.
1 More On Dynamic programming Algorithms Shortest path with edge constraint: Let G=(V, E) be a directed graph with weighted edges. Let s and v be two vertices.
Lecture 38 CSE 331 Dec 3, A new grading proposal Towards your final score in the course MAX ( mid-term as 25%+ finals as 40%, finals as 65%) .
chapter chapter chapter253.
Week 2: Greedy Algorithms
Lecture 7: Greedy Algorithms II
9/3/10 A. Smith; based on slides by E. Demaine, C. Leiserson, S. Raskhodnikova, K. Wayne Guest lecturer: Martin Furer Algorithm Design and Analysis L ECTURE.
computer
CSCI-256 Data Structures & Algorithm Analysis Lecture Note: Some slides by Kevin Wayne. Copyright © 2005 Pearson-Addison Wesley. All rights reserved. 8.
Greedy Methods and Backtracking Dr. Marina Gavrilova Computer Science University of Calgary Canada.
Greedy Algorithms Input: Output: Objective: - make decisions “greedily”, previous decisions are never reconsidered Optimization problems.
CSCI 256 Data Structures and Algorithm Analysis Lecture 6 Some slides by Kevin Wayne copyright 2005, Pearson Addison Wesley all rights reserved, and some.
Managerial Accounting
CSE 421 Algorithms Richard Anderson Lecture 27 NP-Completeness and course wrap up.
Approaches to Problem Solving greedy algorithms dynamic programming backtracking divide-and-conquer.
WEEK 1 You have 10 seconds to name…
Algorithm Design Methods 황승원 Fall 2011 CSE, POSTECH.
CSCI-256 Data Structures & Algorithm Analysis Lecture Note: Some slides by Kevin Wayne. Copyright © 2005 Pearson-Addison Wesley. All rights reserved. 3.
親愛的吉姆舅舅: 今天吃完晚餐後,奶奶說,在家 裡情況變好以前,您要我搬到城裡跟 您住。奶奶有沒有跟您說,爸爸已經 好久沒有工作,也好久沒有人請媽媽 做衣服了? 我們聽完都哭了,連爸爸也哭了, 但是媽媽說了一個故事讓我們又笑了。 她說:您們小的時候,她曾經被您追 得爬到樹上去,真的嗎? 雖然我個子小,但是我很強壯,
Greedy Algorithms – Chapter 5
Chapter 8 Local Ratio II. More Example
Piyush Kumar (Lecture 1: Introduction)
Nelson Mandela Quotes.
Homework: Maintenance Sheet 17 *Due Thursday
Design and Analysis of Algorithm
ASSIGNMENT NO.-2.
Presented by Po-Chuan & Chen-Chen 2016/03/08
CS38 Introduction to Algorithms
Prepared by Chen & Po-Chuan 2016/03/29
در تجزیه و تحلیل شغل باید به 3 سوال اساسی پاسخ دهیم Job analysis تعریف کارشکافی، مطالعه و ثبت جنبه های مشخص و اساسی هر یک از مشاغل عبارتست از مراحلی.
AQR Unit 7 Discrete Mathematics
10:00.
Week of March th grade.
Lecture 11 Overview Self-Reducibility.
Lecture 11 Overview Self-Reducibility.
Richard Anderson Lecture 30 NP-Completeness
Weighted Interval Scheduling
Richard Anderson Lecture 6 Greedy Algorithms
Statistics Lecture 12.
Richard Anderson Autumn 2016 Lecture 7
March 13-17, th Grade Schedule
Richard Anderson Lecture 7 Greedy Algorithms
Backtracking with addition and subtraction
Richard Anderson Lecture 26 NP-Completeness
Math 5-4: Warm-up.
2019/4/10 chapter25.
Lecture 36 CSE 331 Nov 28, 2011.
Lecture 36 CSE 331 Nov 30, 2012.
Weighted Interval Scheduling
Topic 12 Week 28 March 6, 2019.
Midterm: week 7 in the lecture for 2 hours
Richard Anderson Winter 2019 Lecture 7
Analysis of Algorithms CS 477/677
Week 2: Greedy Algorithms
Topic 14 Algorithm Families.
The End is just around the corner!
The End is just around the corner!
CGS 3763 Operating Systems Concepts Spring 2013
A random experiment gives rise to possible outcomes, but any particular outcome is uncertain – “random”. For example, tossing a coin… we know H or T will.
Richard Anderson Autumn 2019 Lecture 7
Presentation transcript:

Assignment 2: Due Week 11, Friday Question 1: For the weighted interval scheduling problem, there are eight jobs with starting time and finish time as follows: j1=(0, 6), j2=(2, 3), j3=(3, 5), j4=(5, 9), j5=(8, 12), j6=(9, 11), j7=(10, 13) and j8=(11, 16). The weight for each job is as follows: v1=3.8, v2=2.0, v3=3.0, v4=3.0, v5=6.5, v6=2.5, v7=13.0, and v8=6.0. Find a maximum weight subset of mutually compatible jobs. (Backtracking process is required.) (You have to compute p()’s. The process of computing p()’s is NOT required.) Question 2: Let X=aabbacab and Y=baabcbb. Find the longest common subsequence for X and Y. (Backtracking process is required.) Question 3. Let X=aabbacab and Y=baabcbb. Find the shortest common supsequence for X and Y. (Backtracking process is required.) 2019/2/5 chapter25