(This article was first published on CYBAEA Data and Analysis, and kindly contributed to Rbloggers)
David posts a question about how to solve this knapsack problem using the R statistical computing and analysis platform. My reply in the comments seems to have disappeared for a while so here is my proposed solution. See David’s blog for my earlier proposed solution with a very common error.
## http://blog.revolutioncomputing.com/2009/07/becauseitsfridaytheknapsackproblem.html appetizer.solution < local ( function (target) { app < c(2.15, 2.75, 3.35, 3.55, 4.20, 5.80) r < 2L repeat { c < gtools::combinations(length(app), r=r, v=app, repeats.allowed=TRUE) s < rowSums(c) if ( all(s > target) ) { print("No solution found") break } x < which( abs(starget) < 1e4 ) if ( length(x) > 0L ) { cat("Solution found: ", c[x,], "\n") break } r < r + 1L } }) appetizer.solution(15.05) # Solution found: 2.15 3.55 3.55 5.8
Brute force works, it just doesn’t scale well. (Note that 7×2.15 is another solution.)
Jump to comments.
You may also like these posts:

Employee productivity as function of number of workers revisitedWe have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is mildly scary. We revisit the analysis …
To leave a comment for the author, please follow the link and comment on his blog: CYBAEA Data and Analysis.
Rbloggers.com offers daily email updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...