Competitive Analysis of a Better On-line Algorithm to Minimize Total Completion Time on a Single-machine

Abstract

We consider the problem of scheduling jobs on-line on a single machine with the objective of minimizing total completion time. We assume that jobs arrive over time and that release dates are known in advance, but not the processing times. The most important result we are given in this paper is the competitive analysis of a new clairvoyant on-line algorithm for this scheduling problem. We are proving that this deterministic semi-online algorithm, called ST-α, is \sqrt3-competitive, which beats the existing lower bound for non-clairvoyant online algorithms.