Scheduling to minimize average completion time: off-line and on-line approximation algorithms
Mathematics of Operations Research
Scheduling Unrelated Machines by Randomized Rounding
SIAM Journal on Discrete Mathematics
Single Machine Scheduling with Release Dates
SIAM Journal on Discrete Mathematics
Optimal On-Line Algorithms for Single-Machine Scheduling
Proceedings of the 5th International IPCO Conference on Integer Programming and Combinatorial Optimization
Improved Scheduling Algorithms for Minsum Criteria
ICALP '96 Proceedings of the 23rd International Colloquium on Automata, Languages and Programming
Competitive Analysis of Algorithms
Developments from a June 1996 seminar on Online algorithms: the state of the art
Online Scheduling of a Single Machine to Minimize Total Weighted Completion Time
Mathematics of Operations Research
Mathematical Programming: Series A and B
An Experimental Study of LP-Based Approximation Algorithms for Scheduling Problems
INFORMS Journal on Computing
Computation of approximate α-points for large scale single machine scheduling problem
Computers and Operations Research
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
LP-based online scheduling: from single to parallel machines
Mathematical Programming: Series A and B
On-line scheduling of parallel machines to minimize total completion times
Computers and Operations Research
Information Processing Letters
Online scheduling of weighted equal-length jobs with hard deadlines on parallel machines
Computers and Operations Research
Efficient algorithms for average completion time scheduling
IPCO'10 Proceedings of the 14th international conference on Integer Programming and Combinatorial Optimization
On-line scheduling to minimize average completion time revisited
Operations Research Letters
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The identical parallel machine scheduling problem with the objective of minimizing total weighted completion time is considered in the online setting where jobs arrive over time. An online algorithm is proposed and is proven to be (2.5-1/2m)-competitive based on the idea of instances reduction. Further computational experiments show the superiority over other algorithms in the average performance.