Score: 1

Scheduling Problems with Constrained Rejections

Published: October 31, 2025 | arXiv ID: 2511.00184v1

By: Sami Davies, Venkatesan Guruswami, Xuandi Ren

BigTech Affiliations: University of California, Berkeley

Potential Business Impact:

Schedules more jobs by slightly delaying some.

Business Areas:
Scheduling Information Technology, Software

We study bicriteria versions of Makespan Minimization on Unrelated Machines and Santa Claus by allowing a constrained number of rejections. Given an instance of Makespan Minimization on Unrelated Machines where the optimal makespan for scheduling $n$ jobs on $m$ unrelated machines is $T$, (Feige and Vondr\'ak, 2006) gave an algorithm that schedules a $(1-1/e+10^{-180})$ fraction of jobs in time $T$. We show the ratio can be improved to $0.6533>1-1/e+0.02$ if we allow makespan $3T/2$. To the best our knowledge, this is the first result examining the tradeoff between makespan and the fraction of scheduled jobs when the makespan is not $T$ or $2T$. For the Santa Claus problem (the Max-Min version of Makespan Minimization), the analogous bicriteria objective was studied by (Golovin, 2005), who gave an algorithm providing an allocation so a $(1-1/k)$ fraction of agents receive value at least $T/k$, for any $k \in \mathbb{Z}^+$ and $T$ being the optimal minimum value every agent can receive. We provide the first hardness result by showing there are constants $\delta,\varepsilon>0$ such that it is NP-hard to find an allocation where a $(1-\delta)$ fraction of agents receive value at least $(1-\varepsilon) T$. To prove this hardness result, we introduce a bicriteria version of Set Packing, which may be of independent interest, and prove some algorithmic and hardness results for it. Overall, we believe these bicriteria scheduling problems warrant further study as they provide an interesting lens to understand how robust the difficulty of the original optimization goal might be.

Country of Origin
🇺🇸 United States

Page Count
18 pages

Category
Computer Science:
Data Structures and Algorithms