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. S...

Scheduling problems are fundamental in combinatorial optimization. Much work has been done on approximation algorithms for NP-hard cases, but relatively little is known about exact solutions when some part of the input is a fixed parameter. In 2014, Mnich and Wiese initiated a systematic study in this direction. In this paper we continue this study and show that several additional cases of fund...

In this paper we generalize the concept of verification introduced by Nisan and Ronen [STOC 1999]. We assume to have selfish agents with general valuation functions and we study mechanisms with verification for optimization problems with these selfish agents. We provide a technique for designing truthful mechanisms with verification that optimally solve the underlying optimization problem. Our ...

Multicore shared cache processors pose a challenge for designers of embedded systems who try to achieve minimal and predictable execution time of workloads consisting of several jobs. One way in which this challenge was addressed is by statically partitioning the cache among the cores and assigning the jobs to the cores with the goal of minimizing the makespan. Several heuristic algorithms have...

We consider the problem of online scheduling of jobs on unrelated machines with dynamic speed scaling to minimize the sum of energy and weighted flow time. We give an algorithm with an almost optimal competitive ratio for arbitrary power functions. (No earlier results handled arbitrary power functions for unrelated machines.) For power functions of the form f(s) = s for some constant α > 1, we ...

The parallel mechine scheduling problem with unrelated machines is studied where the objective is to minimize the maximum makespan. In this paper, new local search algorithms are proposed where the neighborhood search of a solution uses the “efficiency” of the machinea for each job. It is shown that this method yields better solutions and shorter running times than the more general local search...