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Simultaneous job scheduling and resource allocation on parallel machines. Working Paper (1999)

by Z-L Chen
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Scheduling Parallel Jobs with Linear Speedup

by Er Grigoriev, Marc Uetz
"... Abstract We consider a scheduling problem where a set of jobs is apriori distributed over parallel machines. The processing time of any job is dependent on the usage of a scarce renewable resource, e.g. personnel. An amount of k units of that resource can be allocated to the jobs at any time, and th ..."
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Abstract We consider a scheduling problem where a set of jobs is apriori distributed over parallel machines. The processing time of any job is dependent on the usage of a scarce renewable resource, e.g. personnel. An amount of k units of that resource can be allocated to the jobs at any time, and the more of that resource is allocated to a job, the smaller its processing time. The dependence of processing times on the amount of resources is linear for any job. The objective is to find a resource allocation and a schedule that minimizes the makespan. Utilizing an integer quadratic programming relaxation, we show how to obtain a (3 + ε)approximation algorithm for that problem, for any ε> 0. This generalizes and improves previous results, respectively. Our approach relies on a fully polynomial time approximation scheme to solve the quadratic programming relaxation. This result is interesting in itself, because the underlying quadratic program is NP-hard to solve. We also derive lower bounds, and discuss further generalizations of the results.

A 3/2-Approximation Algorithm for Parallel Machine Scheduling . . .

by Feng Zhang, Guochun Tanga , et al. , 2001
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Acknowledgements This graduation thesis is the result of a seven-month internship at TNO Telecom in

by Ir. B. M. M. Gijsen, Drs F. Phillipson Mtd
"... Sojourn times in a two-layered tandem queue with limited service positions and a shared processor Wemke van der Weij ..."
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Sojourn times in a two-layered tandem queue with limited service positions and a shared processor Wemke van der Weij
The National Science Foundation
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