Combinatorial optimization | Dynamic programming | NP-complete problems | Packing problems | Pseudo-polynomial time algorithms
The quadratic knapsack problem (QKP), first introduced in 19th century, is an extension of knapsack problem that allows for quadratic terms in the objective function: Given a set of items, each with a weight, a value, and an extra profit that can be earned if two items are selected, determine the number of items to include in a collection without exceeding capacity of the knapsack, so as to maximize the overall profit. Usually, quadratic knapsack problems come with a restriction on the number of copies of each kind of item: either 0, or 1. This special type of QKP forms the 0-1 quadratic knapsack problem, which was first discussed by Gallo et al.The 0-1 quadratic knapsack problem is a variation of knapsack problems, combining the features of unbounded knapsack problem, 0-1 knapsack problem and quadratic knapsack problem. (Wikipedia).
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
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
How to solve a quadratic using the quadratic formula
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Recitation 21: Dynamic Programming: Knapsack Problem
MIT 6.006 Introduction to Algorithms, Fall 2011 View the complete course: http://ocw.mit.edu/6-006F11 Instructor: Victor Costan License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.006 Introduction to Algorithms, Fall 2011
Optimization-Friendly Generic Mechanisms Without Money - Mark Braverman
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From playlist Quadratics
CSE373 2012 - Lecture 02 - Big-O Notation (Asymptotic Notation)
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From playlist CSE373 - Analysis of Algorithms - 2012 SBU
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Powered by https://www.numerise.com/ Solving past AQA past paper question www.hegartymaths.com http://www.hegartymaths.com/
From playlist Quadratic Equations (GCSE Tutorials)
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From playlist Solve by Quadratic Formula | ax^2+bx+c
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From playlist Solve by Quadratic Formula | ax^2+bx+c
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From playlist Solve by Quadratic Formula | ax^2+bx+c
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From playlist Solve by Quadratic Formula | ax^2+bx+c
Lecture 21: Dynamic Programming III: Parenthesization, Edit Distance, Knapsack
MIT 6.006 Introduction to Algorithms, Fall 2011 View the complete course: http://ocw.mit.edu/6-006F11 Instructor: Erik Demaine License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 6.006 Introduction to Algorithms, Fall 2011
Stanford Seminar - Decision Making at Scale: Algorithms, Mechanisms, and Platforms
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From playlist Math for Liberal Studies Lectures
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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
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