Two approximation algorithms are presented for minimizing the makespan of independant tasks assigned on unrelated machines. The rst one is based upon a partial and heuristical exploration of a search tree, which is used not only to build a solution but also to improve it thanks to a post-optimization procedure. The second implements a new large neighborhood improvement procedure to an already e...

One of the most important open problems in machine scheduling is the problem of scheduling a set of jobs on unrelated machines to minimize the makespan. The best known approximation algorithm for this problem guarantees an approximation factor of 2. It is known to be NP -hard to approximate with a better ratio than 3/2. Closing this gap has been open for over 20 years. The best known approximat...

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

This paper investigates the use of genetic programming in automatized synthesis of heuristics for the parallel unrelated machines environment with arbitrary performance criteria. The proposed scheduling heuristic consists of a manually defined meta-algorithm which uses a priority function evolved separately with genetic programming. In this paper, several different genetic programming methods f...

We study a natural generalization of the problem of minimizing makespan on unrelated machines in which jobs may be split into parts. The different parts of a job can be (simultaneously) processed on different machines, but each part requires a setup time before it can be processed. First we show that a natural adaptation of the seminal approximation algorithm for unrelated machine scheduling [1...

We consider the problem of scheduling n independent jobs on m unrelated parallel machines without preemption. Job i takes processing time pi j on machine j , and the total time used by a machine is the sum of the processing times for the jobs assigned to it. The objective is to minimize makespan. The best known approximation algorithms for this problem compute an optimum fractional solution and...

Motivated by problems in distributed computing, this thesis presents the first nontrivial polynomial time approximation algorithms for an important class of machine scheduling problems. We study the family of preemptive minimum makespan scheduling problems where jobs have stochastic processing requirements and provide the first approximation algorithms for these problems when machines have unre...

http://dx.doi.org/10.1016/j.cie.2014.05.012 0360-8352/ 2014 Elsevier Ltd. All rights reserved. q This manuscript was processed by Area Editor Hans Kellerer. ⇑ Corresponding author. Address: Department of Industrial Management, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei 106, Taiwan. Tel.: +886 2 2737 6337. E-mail address: [email protected] (C....

In this research we address a sequence-dependent group scheduling problem on a set of unrelated-parallel machines where the run time of each job differs on different machines. To benefit both producer and customers we attempt to minimize a linear combination of total weighted completion time and total weighted tardiness. Since the problem is shown to be NP-hard, meta-heuristic algorithms based ...

In this paper we study the unrelated parallel machines problem where n independent jobs must be assigned to one out of m parallel machines and the processing time of each job differs from machine to machine. We deal with the objective of the minimisation of the maximum completion time of the jobs, usually referred to as makespan or Cmax. This is a type of assignment problem that has been freque...