Fair Repetitive Interval Scheduling

TL;DR

This paper studies a fair repetitive scheduling problem where clients submit daily jobs with specific time intervals, aiming to ensure each client is served at least k days, highlighting its NP-hardness and proposing efficient solutions for special cases.

Contribution

The paper introduces a new repetitive scheduling model focused on fairness, proves its NP-hardness, and offers efficient algorithms for specific scenarios and parameterized analysis.

Findings

Problem is NP-hard even with identical processing times.

Efficient algorithms exist for certain special cases.

Parameter analysis reveals both hardness and tractability results.

Abstract

Fair resource allocation is undoubtedly a crucial factor in customer satisfaction in several scheduling scenarios. This is especially apparent in repetitive scheduling models where the same set of clients repeatedly submits jobs on a daily basis. In this paper, we aim to analyze a repetitive scheduling system involving a set of $n$ clients and a set of $m$ days. On every day, each client submits a request to process a job exactly within a specific time interval, which may vary from day to day, modeling the scenario where the scheduling is done Just-In-Time (JIT). The daily schedule is executed on a single machine that can process a single job at a time, therefore it is not possible to schedule jobs with intersecting time intervals. Accordingly, a feasible solution corresponds to sets of jobs with disjoint time intervals, one set per day. We define the quality of service (QoS) that a client receives as the number of executed jobs over the $m$ days period. Our objective is to provide a feasible solution where each client has at least $k$ days where his jobs are processed. We prove that this problem is NP-hard even under various natural restrictions such as identical processing times and day-independent due dates. We also provide efficient algorithms for several special cases and analyze the parameterized tractability of the problem with respect to several parameters, providing both parameterized hardness and tractability results.