Improved results for data migration and open shop scheduling
ACM Transactions on Algorithms (TALG)
Models and Algorithms for Stochastic Online Scheduling
Mathematics of Operations Research
Approximation in preemptive stochastic online scheduling
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Stochastic Online Scheduling Revisited
COCOA 2008 Proceedings of the 2nd international conference on Combinatorial Optimization and Applications
An improved quantum genetic algorithm for stochastic job shop problem
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Computers and Operations Research
A priori parallel machines scheduling
Computers and Industrial Engineering
Computers and Operations Research
A stochastic scheduling algorithm for precedence constrained tasks on Grid
Future Generation Computer Systems
Adaptive Uncertainty Resolution in Bayesian Combinatorial Optimization Problems
ACM Transactions on Algorithms (TALG)
Sampling and Cost-Sharing: Approximation Algorithms for Stochastic Optimization Problems
SIAM Journal on Computing
List scheduling in order of α-points on a single machine
Efficient Approximation and Online Algorithms
Approximation algorithms for scheduling problems with a modified total weighted tardiness objective
Operations Research Letters
Minimizing conditional-value-at-risk for stochastic scheduling problems
Journal of Scheduling
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We consider parallel, identical machine scheduling problems, where the jobs are subject to precedence constraints and release dates, and where the processing times of jobs are governed by independent probability distributions. Our objective is to minimize the expected value of the total weighted completion time. Building upon a linear programming relaxation by Möhring, Schulz, and Uetz [J. ACM, 46 (1999), pp. 924--942] and a delayed list scheduling algorithm by Chekuri et al. [SIAM J. Comput., 31 (2001), pp. 146--166], we derive the first constant-factor approximation algorithms for this model.