100% satisfaction guarantee Immediately available after payment Both online and in PDF No strings attached
logo-home
Previously searched by you
Previously searched by you
logo
CO2412 Computational Thinking Lecture 7 Notes CA$6.39   Add to cart
Quickly navigate to
Preview
  2.  
  3. University Of Central Lancashire Preston (UClan)
  4.  
  5. Computational Thinking (CO2412)

Class notes

CO2412 Computational Thinking Lecture 7 Notes
 5 views  0 purchase
  • Course
  • Computational Thinking (CO2412)
  • Institution
  • University Of Central Lancashire Preston (UClan)

This document contains comprehensive notes from Lecture 7 of the CO2412 course on Computational Thinking. The lecture explores two important strategies for solving optimization problems: Greedy Algorithms and the Branch and Bound method. It provides an in-depth understanding of how these approaches...

[Show more]

Preview 1 out of 3  pages

Document information

  • August 20, 2024
  • 3
  • 2023/2024
  • Class notes
  • Amin amini
  • All classes

Subjects

  • computer science
  • computational
  • python
  • algorithms
  • university
  • computer
  • 2nd year
  • efficiency
  • lecture
  • cs
  • notes

Written for

  • University of Central Lancashire Preston (UClan)
  • Unknown
  • Computational Thinking (CO2412)
All documents for this subject (19)

Seller

avatar-seller
BpoBpo

Reviews received

Content preview

CO2412: Computational Thinking
Lecture 7

The Greedy Algorithm
1. Introduction
o A greedy algorithm follows the problem-solving heuristic of making
the locally optimal choice at each stage with the hope of finding the
global optimum.
o Greedy algorithms are typically used for optimization problems.

2. Characteristics of Greedy Algorithms
o Local Optimization: The algorithm selects the best option
available at each step without considering the broader context.
o Greedy Choice Property: It assumes that by choosing the optimal
local solution, the global solution will also be optimal.
o Optimal Substructure: The problem can be broken down into
smaller subproblems, which can be solved optimally.
Fractional Knapsack Problem
1. Problem Statement
o The Fractional Knapsack problem involves a thief who can carry a
maximum weight in their knapsack. The goal is to maximize the
value of the knapsack by taking fractions of items.
2. Greedy Approach to Fractional Knapsack
o Items are selected based on the highest value-to-weight ratio.

o The item with the highest ratio is taken first, followed by the next,
and so on, until the knapsack is full.
Example:

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller BpoBpo. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for CA$6.39. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

62890 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 14 years now

Start selling
CA$6.39
  • (0)
  Add to cart