npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

iterative-greedy

v1.0.0

Published

Generic implementation of iterative greedy algorithm

Downloads

155

Readme

Iterative Greedy

Generic implementation of iterative greedy

What is?

A way to boost a greedy algorithm in order to obtain a more extensive solution.

Concrete example

Consider the following task: Given a collection of arrays of numbers, pick an element from each of the arrays such that there aren't two equal elements and such that the sum is maximized. That is, given two arrays [1, 4] and [2, 4], we should return 4 from the first array and 2 from the second. The only way to obtain a better sum would be with 4, 4 but then the elements would be repeated.

There is an easy way to solve the problem in general, just go over all the possible combination of elements and pick the one that maximizes the sum. This is obviously non feasible since the complexity is O(m^n).

A greedy algorithm for the task would go as follows, pick the maximum element of the first array, then the maximum element from the next array which is not equal, go on with the following skipping arrays when all elements have already been chosen. In the case above, the maximum element from the first array is 4 so we pick it, in the second array 4 is already taken so we pick 2 and we are done.

Now, let's add another array, also with elements [4, 2], that is we start with arrays [1,4], [2,4] and [2,4]. The algorithm wouldn't be able to pick any element from the third array because 2 and 4 have been already chosen.

Presenting iterative greedy: Apply iteratively a greedy algorithm, if an element cannot be used in one iteration promote it so that it is evaluated first in the following iteration. In our example, after the first pass [2, 4] is not used so we promote it. In the second pass we first apply the greedy algorithm to it, obtaining 4. Then we go to [1, 4] and [2, 4] with 4 already chosen. We pick 1 and 2 and we end up with 4, 1, 2 which is a better result than the 4, 2 obtained with the simple greedy.