Scheduling with Machine Conflicts

TL;DR

This paper investigates the complexity of scheduling jobs with machine conflicts, showing hardness results, providing approximation algorithms under certain conditions, and solving special cases efficiently.

Contribution

It establishes NP-hardness and approximation bounds for SchedulingWithMachineConflicts, and offers polynomial algorithms for specific graph classes and job types.

Findings

No polynomial approximation within factor m^{1-ε} unless P=NP.

Approximation algorithms exist with given independent sets.

Polynomial algorithms for unit jobs on bipartite and star forest conflict graphs.

Abstract

We study the scheduling problem of makespan minimization while taking machine conflicts into account. Machine conflicts arise in various settings, e.g., shared resources for pre- and post-processing of tasks or spatial restrictions. In this context, each job has a blocking time before and after its processing time, i.e., three parameters. We seek for conflict-free schedules in which the blocking times of no two jobs intersect on conflicting machines. Given a set of jobs, a set of machines, and a graph representing machine conflicts, the problem SchedulingWithMachineConflicts (SMC), asks for a conflict-free schedule of minimum makespan. We show that, unless $\textrm{P}=\textrm{NP}$, SMC on $m$ machines does not allow for a $\mathcal{O}(m^{1-\varepsilon})$-approximation algorithm for any $\varepsilon>0$, even in the case of identical jobs and every choice of fixed positive parameters, including the unit case. Complementary, we provide approximation algorithms when a suitable collection of independent sets is given. Finally, we present polynomial time algorithms to solve the problem for the case of unit jobs on special graph classes. Most prominently, we solve it for bipartite graphs by using structural insights for conflict graphs of star forests.