In this paper we study two generalizations of the well known unrelated parallel machines scheduling problem under makespan (Cmax) minimization. First, a situation in which not every available parallel machine should be used and it is desirable to employ only a subset of the parallel machines. This is referred to as “Not all Machines” or NAM in short. This environment applies frequently in produ...

When a computer system schedules jobs there is typically significant cost associated with preempting job during execution. This can be incurred from the expensive task of saving memory’s state or loading data into and out memory. Thus, it desirable to schedule non-preemptively avoid costs preemption. There need for non-preemptive schedulers desktops, servers, centers. Despite this need, gap bet...

In this paper, we provide a new class of randomized approximation algorithms for parallel machine scheduling problems. The most general model we consider is scheduling unrelated machines with release dates (or even network scheduling) so as to minimize the average weighted completion time. We introduce an LP relaxation in time-indexed variables for this problem. The crucial idea to derive appro...

We investigate coordination mechanisms that schedule n jobs on m unrelated machines. The objective is to minimize the latest completion of all jobs, i.e., the makespan. It is known that if the mechanism is non-preemptive, the price of anarchy is Ω(logm). Both Azar, Jain, and Mirrokni (SODA 2008) and Caragiannis (SODA 2009) raised the question whether it is possible to design a coordination mech...

A very well-known machine model in scheduling allows the machines to be unrelated, modelling jobs that might have different characteristics on each machine. Due to its generality, many optimization problems of this form are very difficult to tackle and typically APX-hard. However, in many applications the number of different types of machines, such as processor cores, GPUs, etc. is very limited...

We derive the first performance guarantees for a combinatorial online algorithm that schedules stochastic, nonpreemptive jobs on unrelated machines to minimize the expectation of the total weighted completion time. Prior work on unrelated machine scheduling with stochastic jobs was restricted to the offline case, and required sophisticated linear or convex programming relaxations for the assign...

In this paper, we study the unrelated parallel machine problem for minimizing the makespan, which is NP-hard. We used Simulated Annealing (SA) and Tabu Search (TS) with Neighborhood Search (NS) based on the structure of the problem. We also used a modified SA algorithm, which gives better results than the traditional SA and developed an effective heuristic for the problem: Squeaky Wheel Optimiz...

We consider the problem of minimizing general delay costs on unrelated machines. In this problem, we are given a set of m machines and a set of n jobs. Each job j has a machine dependent processing time of pij on machine i, and a release time rij . Further, we are also given a non-decreasing function fj(t) which gives the cost of completing the job j at time t. Our goal is to assign each job to...