Combinatorial optimization

List of knapsack problems

The knapsack problem is one of the most studied problems in combinatorial optimization, with many real-life applications. For this reason, many special cases and generalizations have been examined. Common to all versions are a set of n items, with each item having an associated profit pj and weight wj. The binary decision variable xj is used to select the item. The objective is to pick some of the items, with maximal total profit, while obeying that the maximum total weight of the chosen items must not exceed W. Generally, these coefficients are scaled to become integers, and they are almost always assumed to be positive. The knapsack problem in its most basic form: (Wikipedia).

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0/1 Knapsack problem | Dynamic Programming

Overview of the 0/1 Knapsack problem using dynamic programming Algorithms repository: https://github.com/williamfiset/algorithms My website: http://www.williamfiset.com

From playlist Dynamic Programming

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0-1 Knapsack Problem (Dynamic Programming)

Dynamic Programming Tutorial with 0-1 Knapsack Problem

From playlist Dynamic Programming Tutorial Series

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Math for Liberal Studies - Lecture 1.9 The Knapsack Problem

This video covers material from Math for Liberal Studies Section 1.9: The Knapsack Problem. In this video, I explain what the knapsack problem is, and we work through an example using a recursive algorithm to solve the problem.

From playlist Math for Liberal Studies Lectures

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Knapsack Problem Using Dynamic Programming | 0/1 Knapsack Problem | Data Structures | Simplilearn

This video on knapsack Problem Using Dynamic Programming will acquaint you with a clear understanding of the fractional or 0-1 knapsack problem statement and solution implementation. In this Data Structure Tutorial, you will understand why the difference between 0-1 knapsack and fractional

From playlist Data Structures & Algorithms

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Dynamic Programming 1 [Programming Competition Problems]

Source code: http://problemvault.com/index.php#problem127 Problem source / Online judge: https://open.kattis.com/problems/knapsack This video explores a classic dynamic programming problem known as the "0/1 Knapsack Problem". We walk through how the algorithm works, then we go ahead and i

From playlist Programming Competition Problems with Micah Stairs

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Problem #3 - Swinging Pendulum

Problem #3 - Swinging Pendulum

From playlist Bi-weekly Physics Problems

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Turing Machines and The Halting Problem (Part 2)

The Halting Problem has fascinated thousands of computer scientists from around the world. A major part of Computing Logic, the proof of the halting problem proves that computers can't do everything. Check out the video to learn more about why computers work the way they do! For Turing Ma

From playlist Math

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Equilateral Triangles Problem

GeoGebra Link: https://www.geogebra.org/m/f5zgupmz

From playlist Geometry: Challenge Problems

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Knapsack, Bandwidth Min. Intro: Greedy Algorithms - Lecture 14

All rights reserved for http://www.aduni.org/ Published under the Creative Commons Attribution-ShareAlike license http://creativecommons.org/licenses/by-sa/2.0/ Tutorials by Instructor: Shai Simonson. http://www.stonehill.edu/compsci/shai.htm Visit the forum at: http://www.coderisland.c

From playlist ArsDigita Algorithms by Shai Simonson

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Lec 14 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Lecture 14: Analysis of knapsack problem, introduction to object-oriented programming Instructors: Prof. Eric Grimson, Prof. John Guttag View the complete course at: http://ocw.mit.edu/6-00F08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at

From playlist MIT 6.00 Intro to Computer Science & Programming, Fall 2008

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1. Introduction, Optimization Problems (MIT 6.0002 Intro to Computational Thinking and Data Science)

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: John Guttag Prof. Guttag provides an overview of the course and discusses how we use computational models to understand the world in which we li

From playlist MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016

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Lec 18 | MIT 6.00SC Introduction to Computer Science and Programming, Spring 2011

Lecture 18: Optimization Problems and Algorithms Instructor: John Guttag View the complete course: http://ocw.mit.edu/6-00SCS11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 6.00SC Introduction to Computer Science and Programming

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Lecture 26 - The NP-Completeness Challenge

This is Lecture 26 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www3.cs.stonybrook.edu/~skiena/] at Stony Brook University in 2016. The lecture slides are available at: https://www.cs.stonybrook.edu/~skiena/373/newlectures/lecture22.pdf More inf

From playlist CSE373 - Analysis of Algorithms 2016 SBU

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The Corner Cube Problem

The corner cube problem is interesting because it initially looks difficult. When the problem was first posed to me, for example, it didn't know how to solve it. Still, my intuition bells were ringing, telling me there was a nice solution. In this video, I cover two of these solutions, in

From playlist Fun

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Lec 12 | MIT 6.00 Introduction to Computer Science and Programming, Fall 2008

Lecture 12: More about debugging, knapsack problem, introduction to dynamic programming Instructors: Prof. Eric Grimson, Prof. John Guttag View the complete course at: http://ocw.mit.edu/6-00F08 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms Mor

From playlist MIT 6.00 Intro to Computer Science & Programming, Fall 2008

Related pages

Combinatorial optimization | Knapsack problem | Pseudo-polynomial time | Quadratic knapsack problem | Polynomial-time approximation scheme | Assignment problem | Decision problem | Cutting stock problem | Subset sum problem | Bin packing problem