Seung Gu Kang, Jeff Weber, et al.
ACS Fall 2023
We study the scheduling situation where n tasks, subjected to release dates and due dates, have to be scheduled on m parallel processors. We show that, when tasks have unit processing times and either require 1 or m processors simultaneously, the minimum maximal tardiness can be computed in polynomial time. Two algorithms are described. The first one is based on a linear programming formulation of the problem while the second one is a combinatorial algorithm. The complexity status of this "tall/small" task scheduling problem P|r i,p i = 1, size i ∈ {1, m}|T max was unknown before, even for two processors.
Seung Gu Kang, Jeff Weber, et al.
ACS Fall 2023
Saeel Sandeep Nachane, Ojas Gramopadhye, et al.
EMNLP 2024
Tim Erdmann, Stefan Zecevic, et al.
ACS Spring 2024
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence