1985•Unpublished venueRequires access

Randomized Rounding: A Technique for Provably Good Algorithms and

Prabhakar Raghavan, Clark D. Thompson

Abstract

We study the relation between a class of 0-1 integer linear programs and their rational relaxations. We show that the rational optimum to a problem instance can be used to construct a provably good 0-1 solution by means of a randomized algorithm. Our technique can be extended to provide bounds on the disparity between the rational and 0-1 optima for a given problem instance.

About this research paper

What this paper is about

Why it matters

OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Key concepts: Rounding, Algorithm, Class (philosophy), Randomized algorithm, Construct (python library), Mathematics, Integer (computer science), Randomized rounding