Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the sizes of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated machine scheduling model with stochastic processing times of jobs. By means of a novel time-indexed linear ...

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...

Let there be m parallel machines and n jobs, where a job j can be scheduled on machine i to take pi, j ∈ Z+ time units. The makespan Cmax is the completion time of a machine that finishes last. The goal is to produce a schedule with all n jobs that has minimum makespan. This is the makespan problem on unrelated parallel machines, denoted as R||Cmax. Assume p,q ∈ Z+ are constants, let A(p,q) = {...

In this paper, we propose a multi-criteria machine-schedules decision making method that can be applied to a production environment involving several unrelated parallel machines and we will focus on three objectives: minimizing makespan, total flow time, and total number of tardy jobs. The decision making method consists of three phases. In the first phase, a mathematical model of a single mach...

The goal of this paper is to investigate scheduling heuristics to seek the minimum of a positively weighted convex sum of makespan and the number of tardy jobs in a static hybrid flow shop environment where at least one production stage is made up of unrelated parallel machines. In addition, sequence and machine dependent setup times are considered. The problem is a combinatorial optimization p...

In this paper, we present an industrial problem found in a company that produces acrylic fibres to be used by the textile industry. The problem is a particular case of the discrete lot sizing and scheduling problem (DLSP). In this problem, lots of similar products must be generated and sequenced in ten unrelated parallel machines, in order to minimize tool changeovers and the quantity of fibre ...

The NP-hard problem addressed in this paper is well known in the scheduling literature as Rl( C,,,. We propose lower bounds based on Lagrangian relaxations and additive techniques. We then introduce new cuts which eliminate infeasible disjunctions on the cost function value, and prove that the bounds obtained through such cuts dominate the previous bounds. These results are used to obtain exact...

This paper proposes a novel multi-objective model for an unrelated parallel machine scheduling problem considering inherent uncertainty in processing times and due dates. The problem is characterized by non-zero ready times, sequence and machine-dependent setup times, and secondary resource constraints for jobs. Each job can be processed only if its required machine and secondary resource (if a...