Lecture 3: Greedy algorithms (Adv.) The University of Sydney Page 1 Shortest path trees vs minimum spanning trees Shortest path trees and minimum spanning trees can be very different In tutorial, we saw the following example. Can it be worse? The University of Sydney Page 2 Light approximate shortest path tree (LAST) Given a graph […]
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Lecture 9 – Flow networks II: Applications The University of Sydney Page 1 General techniques in this course – Greedy algorithms [Lecture 3] – Divide & Conquer algorithms [Lectures 4 & 5] – Dynamic programming algorithms [Lectures 6 and 7] – Network flow algorithms [Lecture 8 and today] – Theory [Lecture 8] – Applications [today]
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COMP3027/COMP3927 Tutorial questions The University of Sydney 2019 Semester 1 Tutorial 5 School of Computer Science Tutorial This tutorial will be mostly reviewing greedy and divide-and-conquer algorithms. Please make sure you do Problem 4 as it will be important for next week’s lecture. Problem 1 Suppose we are to schedule print jobs on a printer.
Assignment Definition Suppose you are given a set of n jobs, where each job i has a start time si and finish time fi. We say two jobs i and j conflict if their intervals (si,fi) and (sj,fj) intersect. Your task is to design an algorithm which outputs the maximum size set of jobs such
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Lecture 13: Summary The University of Sydney Page 1 Please remember to fill in the unit of study evaluation – COMP3027: https://student- surveys.sydney.edu.au/students/complete/form.cfm?key=uss22 1795 – COMP3927: https://student- surveys.sydney.edu.au/students/complete/form.cfm?key=uss22 1804 What was good? What was bad? – Tutor and tutorials – Were the extra resources, e.g. exemplars, useful? – Assignments, feedback The University of Sydney Page
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COMP3027/COMP3927 Tutorial questions The University of Sydney 2019 Semester 1 Tutorial 6 School of Computer Science Pre-tutorial questions Do you know the basic concepts of this week’s lecture content? These questions are only to test yourself. They will not be explicitly discussed in the tutorial, and no solutions will be given to them. 1. Dynamic
Algorithms Jeff Erickson 0th edition (pre-publication draft) — December 29, 2018 0 1 2 3 4 5 6 7 8 9 — 27 26 25 24 23 22 21 20 19 18 © Copyright 2019 Jeff Erickson cb This work is available under a Creative Commons Attribution 4.0 International License. For license details, see http://creativecommons.org/licenses/by/4.0/.
COMP3027/COMP3927 Tutorial questions The University of Sydney 2020 Semester 1 Tutorial School of Computer Science 1 Greedy algorithms Greedy algorithms can be some of the simplest algorithms to implement, but they’re often among the hardest algorithms to design and analyze. You can often stumble on the right algorithm but not recognize that you’ve found it,
Algorithms 3027 Assignment 5 The University of Sydney 2019 Semester 1 School of Computer Science This assignment is for COMP3027 students only. Task 1: [40 marks] You are a pirate captain. After looting a cargo ship, you need to divide up the n treasure chests among k pirates in an egalitarian manner to avoid mutiny.
Lecture 10: NP and Computational Intractability II The University of Sydney Page 1 8.3 Definition of NP • Class P • Class NP • Class NP-complete The University of Sydney Page 2 Definition of the class P Class P: Decision problems for which there is a deterministic poly-time algorithm. Problem Description Algorithm Yes No MULTIPLE
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