Efficient algorithms for scheduling semiconductor burn-in operations
Operations Research
Approximation schemes for the restricted shortest path problem
Mathematics of Operations Research
Scheduling to minimize average completion time: off-line and on-line approximation algorithms
Mathematics of Operations Research
Scheduling one batch processor subject to job release dates
Discrete Applied Mathematics
Improved Scheduling Algorithms for Minsum Criteria
ICALP '96 Proceedings of the 23rd International Colloquium on Automata, Languages and Programming
Minimizing mean response time in batch processing system
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
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Scheduling a batch processing system has been extensively studied in the last decade. A batch processing system is modelled as a machine that can process up to b jobs simultaneously as a batch. The scheduling problem involves assigning all n jobs to batches and determining the batch sequence in such a way that certain objective function of job completion times Cj is minimized.In this paper, we address the scheduling problem under the on-line setting in the sense that we construct our schedule irrevocably as time proceeds and do not know of the existence of any job that may arrive later. Our objective is to minimize the total weighted completion time ΣwjCj. We provide a linear time on-line algorithm for the unrestrictive model (i.e., b ≥ n) and show that the algorithm is 10/3-competitive. For the restrictive model (i.e., b n), we first consider the (off-line) problem of finding a maximum independent vertex set in an interval graph with cost constraint (MISCP), which is NP-hard. We give a dual fully polynomial time approximation scheme for MISCP, which leads us to a (4+Ɛ)-competitive on-line algorithm for any Ɛ 0 for the original on-line scheduling problem. These two on-line algorithms are the first deterministic algorithms of constant performance guarantees.