Online scheduling on two parallel machines with release dates and delivery times

Peihai Liu () and Xiwen Lu
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Peihai Liu: East China University of Science and Technology
Xiwen Lu: East China University of Science and Technology

Journal of Combinatorial Optimization, 2015, vol. 30, issue 2, No 9, 347-359

Abstract: Abstract We consider an online scheduling problem where jobs arrive over time. A set of independent jobs has to be scheduled on two parallel machines, where preemption is not allowed and the number of jobs is unknown in advance. The characteristics of each job, i.e., processing time and delivery time, become known at its release date. Each job is delivered to the destination independently and immediately at its completion time on the machines. The objective is to minimize the time by which all jobs have been delivered. We present an online algorithm which has a competitive ratio of $$(1+\sqrt{5})/2\approx 1.618$$ ( 1 + 5 ) / 2 ≈ 1.618 . Finally, our experimental results show that, in practice, the worst case error ratio is much better than the theoretical bound.

Keywords: Scheduling; Delivery times; Parallel machines; Online algorithm (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10878-014-9760-y

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