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In theoretical computer science, the continuous knapsack problem (also known as the fractional knapsack problem) is an algorithmic problem in combinatorial optimization in which the goal is to fill a container (the "knapsack") with fractional amounts of different materials chosen to maximize the value of the selected materials.
The quadratic knapsack problem maximizes a quadratic objective function subject to binary and linear capacity constraints. [36] The problem was introduced by Gallo, Hammer, and Simeone in 1980, [ 37 ] however the first treatment of the problem dates back to Witzgall in 1975.
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. For this reason, many special cases and generalizations have been examined.
For example, it is possible to pack 147 rectangles of size (137,95) in a rectangle of size (1600,1230). Packing different rectangles in a rectangle : The problem of packing multiple rectangles of varying widths and heights in an enclosing rectangle of minimum area (but with no boundaries on the enclosing rectangle's width or height) has an ...
For example, the first fit ... The problem of fractional knapsack with penalties was ... study a setting where the cost of a bin is a concave function of the number ...
Given a knapsack problem, define a PB instance with a single voter in which the budget is the knapsack capacity, and for each item with weight w and value v, there is a project with cost w and utility v. Let P be the optimal solution to the knapsack instance.
The following is the skeleton of a generic branch and bound algorithm for minimizing an arbitrary objective function f. [3] To obtain an actual algorithm from this, one requires a bounding function bound, that computes lower bounds of f on nodes of the search tree, as well as a problem-specific branching rule.
For the one-dimensional case, the new patterns are introduced by solving an auxiliary optimization problem called the knapsack problem, using dual variable information from the linear program. The knapsack problem has well-known methods to solve it, such as branch and bound and dynamic programming. The Delayed Column Generation method can be ...