brute_force_knapsack: Brute force algorithm for solving knapsack problem

In mpirmoradiyan/knapsack: Three approaches to deal with knapsack problem

Description

brute_force_knapsack(x, W) returns the solution for knapsack problem using brute force algorithm.

Usage

brute_force_knapsack(x, W, parallel = FALSE)

Arguments

x	A data.frame with two variables ("w" , "v"). Every observation (row) in this data frame is an item with a weight (w) and a value (v).
W	A numeric scalar which is the maximum capacity of the knapsack.
parallel	If TRUE, the "parallel" package will be implemented to parallelize the function.

Details

This function solves the Knapsack probem using brute force approach. The knapsack problem is a discrete optimization problem where we have a knapsack that can take a limited weight W and we want to fill this knapsack with a number of items i = 1, 2 ,...,n; each with a weight(w) and a value(v). The goal is to find the knapsack with the largest value of the elements added to the knapsack.

Value

A list with names $value, indicating maximum value of the items picked into the the knapsack , and $elements which states which items (rows) in data.frame were selected out to put into the knapsack.

References

http://en.wikipedia.org/wiki/Knapsack_problem

Examples

 brute_force_knapsack(data.frame(w=c(3660,3749,1145,3322),v=c(9899,4384,6999,8890)),W =3500)
 

mpirmoradiyan/knapsack documentation built on Nov. 4, 2019, 7:31 p.m.