Journal
ANNALS OF OPERATIONS RESEARCH
Volume 191, Issue 1, Pages 155-169Publisher
SPRINGER
DOI: 10.1007/s10479-011-0923-2
Keywords
Scheduling; Flow shop; Learning effect; Worst-case analysis
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Funding
- National Natural Science Foundation of China [11001181, 71031002, 70725004]
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A real industrial production phenomenon, referred to as learning effects, has drawn increasing attention. However, most research on this issue considers only single machine problems. Motivated by this limitation, this paper considers flow shop scheduling problems with a general position-dependent learning effects. By the general position-dependent learning effects, we mean that the actual processing time of a job is defined by a general non-increasing function of its scheduled position. The objective is to minimize one of the five regular performance criteria, namely, the total completion time, the makespan, the total weighted completion time, the total weighted discounted completion time, and the sum of the quadratic job completion times. We present heuristic algorithms by using the optimal permutations for the corresponding single machine scheduling problems. We also analyze the worst-case bound of our heuristic algorithms.
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