Streaming approximation scheme for minimizing total completion time on parallel machines subject to varying processing capacity

Authors

Bin Fu, The University of Texas Rio Grande Valley
Yumei Huo, CUNY
Hairong Zhao, Purdue University

Document Type

Article

Publication Date

6-15-2023

Abstract

We study the problem of minimizing total completion time on parallel machines subject to varying processing capacity. In this paper, we develop an approximation scheme for the problem under the data stream model where the input data is massive and cannot fit into memory and thus can only be scanned a few times. Our algorithm can compute an approximate value of the optimal total completion time in one pass and output the schedule with the approximate value in two passes.

Comments

Preprint of the published version available at https://doi.org/10.1016/j.tcs.2023.113937

Recommended Citation

Fu, Bin, Yumei Huo, and Hairong Zhao. "Streaming approximation scheme for minimizing total completion time on parallel machines subject to varying processing capacity." Theoretical Computer Science 961 (2023): 113937. https://doi.org/10.1016/j.tcs.2023.113937

Publication Title

Theoretical Computer Science

DOI

https://doi.org/10.1016/j.tcs.2023.113937