5 research outputs found
On Minimizing the Makespan When Some Jobs Cannot Be Assigned on the Same Machine
We study the classical scheduling problem of assigning jobs to machines in order to minimize the makespan. It is well-studied and admits an EPTAS on identical machines and a (2-1/m)-approximation algorithm on unrelated machines. In this paper we study a variation in which the input jobs are partitioned into bags and no two jobs from the same bag are allowed to be assigned on the same machine. Such a constraint can easily arise, e.g., due to system stability and redundancy considerations. Unfortunately, as we demonstrate in this paper, the techniques of the above results break down in the presence of these additional constraints.
Our first result is a PTAS for the case of identical machines. It enhances the methods from the known (E)PTASs by a finer classification of the input jobs and careful argumentations why a good schedule exists after enumerating over the large jobs. For unrelated machines, we prove that there can be no (log n)^{1/4-epsilon}-approximation algorithm for the problem for any epsilon > 0, assuming that NP nsubseteq ZPTIME(2^{(log n)^{O(1)}}). This holds even in the restricted assignment setting. However, we identify a special case of the latter in which we can do better: if the same set of machines we give an 8-approximation algorithm. It is based on rounding the LP-relaxation of the problem in phases and adjusting the residual fractional solution after each phase to order to respect the bag constraints
Scheduling with Machine Conflicts
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 , SMC on machines does not
allow for a -approximation algorithm for any
, 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.Comment: 20 pages, 8 figure
Total Completion Time Minimization for Scheduling with Incompatibility Cliques
This paper considers parallel machine scheduling with incompatibilities
between jobs. The jobs form a graph and no two jobs connected by an edge are
allowed to be assigned to the same machine. In particular, we study the case
where the graph is a collection of disjoint cliques. Scheduling with
incompatibilities between jobs represents a well-established line of research
in scheduling theory and the case of disjoint cliques has received increasing
attention in recent years. While the research up to this point has been focused
on the makespan objective, we broaden the scope and study the classical total
completion time criterion. In the setting without incompatibilities, this
objective is well known to admit polynomial time algorithms even for unrelated
machines via matching techniques. We show that the introduction of
incompatibility cliques results in a richer, more interesting picture.
Scheduling on identical machines remains solvable in polynomial time, while
scheduling on unrelated machines becomes APX-hard. Furthermore, we study the
problem under the paradigm of fixed-parameter tractable algorithms (FPT). In
particular, we consider a problem variant with assignment restrictions for the
cliques rather than the jobs. We prove that it is NP-hard and can be solved in
FPT time with respect to the number of cliques. Moreover, we show that the
problem on unrelated machines can be solved in FPT time for reasonable
parameters, e.g., the parameter pair: number of machines and maximum processing
time. The latter result is a natural extension of known results for the case
without incompatibilities and can even be extended to the case of total
weighted completion time. All of the FPT results make use of n-fold Integer
Programs that recently have received great attention by proving their
usefulness for scheduling problems