Preemptive Scheduling of Equal-Length Jobs to Maximize Weighted Throughput

TL;DR

This paper presents an efficient O(n^4) algorithm for preemptively scheduling equal-length jobs with release times, deadlines, and weights to maximize total weighted throughput, improving upon previous methods.

Contribution

The authors develop a significantly faster algorithm for a classic scheduling problem, reducing complexity from O(n^{10}) to O(n^4).

Findings

The new algorithm computes optimal schedules efficiently.

It improves the computational complexity of the problem.

The approach advances scheduling theory for weighted throughput maximization.

Abstract

We study the problem of computing a preemptive schedule of equal-length jobs with given release times, deadlines and weights. Our goal is to maximize the weighted throughput, which is the total weight of completed jobs. In Graham's notation this problem is described as (1 | r_j;p_j=p;pmtn | sum w_j U_j). We provide an O(n^4)-time algorithm for this problem, improving the previous bound of O(n^{10}) by Baptiste.