Online Scheduling of Incompatible Family Jobs with Equal Length on an Unbounded Parallel-Batch Machine with Job Delivery

Qijia Liu and Jinjiang Yuan
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Qijia Liu: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, People’s Republic of China2College of Information and Management Science, Henan Agricultural University, Zhengzhou, Henan 450003, People’s Republic of China
Jinjiang Yuan: School of Mathematics and Statistics, Zhengzhou University, Zhengzhou, Henan 450001, People’s Republic of China

Asia-Pacific Journal of Operational Research (APJOR), 2018, vol. 35, issue 04, 1-12

Abstract: In this paper, we consider the online scheduling of incompatible family jobs with equal length on an unbounded parallel-batch machine with job delivery. The jobs arrive online over time and belong to f incompatible job families, where f is known in advance. The jobs are first processed in batches on an unbounded parallel-batch machine and then the completed jobs are delivered in batches by a vehicle with infinite capacity to their customers. The jobs from distinct families cannot be processed and delivered in the same batch. The objective is to minimize the maximum delivery completion time of the jobs. For this problem, we present an online algorithm with the best competitive ratio of 1 + 4f2 +1−1 2f.

Keywords: Scheduling; incompatible family jobs; online algorithm; competitive ratio (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:apjorx:v:35:y:2018:i:04:n:s0217595918500264

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DOI: 10.1142/S0217595918500264

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