Single machine scheduling with past-sequence-dependent setup times and learning effects

Kuo, Wen‐Hung; Yang, Dar-Li

doi:10.1016/j.ipl.2006.11.002

Cited by 72 publications

(30 citation statements)

References 16 publications

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“…The matching algorithm requires O(n log n) time. This algorithm is quite well-known and has become a popular technique for solving scheduling problems in this area; see, e.g., Gawiejnowicz (1996), Kuo and Yang (2007), Oko÷ owski and Gawiejnowicz (2010) and Yang and Yang (2010). Also, see a survey by Rustogi and Strusevich (2012b), which demonstrates that many scheduling problems with changing processing times can be solved by the matching algorithm, but instead less suitable approaches were used in earlier papers.…”

Section: Preliminariesmentioning

confidence: 99%

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

Rustogi

Strusevich

2015

Journal of the Operational Research Society

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We study single machine scheduling problems with linear time-dependent deterioration e¤ects and maintenance activities. Maintenance periods (MPs) are included into the schedule, so that the machine, that gets worse during the processing, can be restored to a better state. We deal with a job-independent version of the deterioration e¤ects, i.e., all jobs share a common deterioration rate. However, we introduce a novel extension to such models and allow the deterioration rates to change after every MP. We study several versions of this generalized problem and design a range of polynomial-time solution algorithms that enable the decision-maker to determine possible sequences of jobs and MPs in the schedule, so that the makespan objective can be minimized. We show that all problems reduce to a linear assignment problem with a product matrix and can be solved by methods very similar to those used for solving problems with positional e¤ects.

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Section: Preliminariesmentioning

confidence: 99%

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

Rustogi

Strusevich

2015

Journal of the Operational Research Society

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“…The matching algorithm requires O(n log n) time. This algorithm is quite well-known and has become a popular technique for solving scheduling problems in this area; see, e.g., [29], [30], [31] and [32]. Also, see a survey [2], which demonstrates that many scheduling problems can be solved by the matching algorithm, but instead less suitable approaches were used in earlier papers.…”

Section: The Solution Approachmentioning

confidence: 99%

Combining time and position dependent effects on a single machine subject to rate-modifying activities

Rustogi

Strusevich

2014

Omega

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Citation for this version held on GALA:Rustogi, Kabir and Strusevich, Vitaly (2014) Combining time and position dependent effects on a single machine subject to rate-modifying activities. London: Greenwich Academic Literature Archive. We introduce a general model for single machine scheduling problems, in which the actual processing times of jobs are subject to a combination of positional and timedependent effects, that are job-independent but additionally depend on certain activities that modify the processing rate of the machine, such as, e.g., maintenance. We focus on minimizing two classical objectives: the makespan and the sum of the completion times. The traditional classification accepted in this area of scheduling is based on the distinction between the learning and deterioration effects, on one hand, and between the positional effects and the start-time dependent effects, on the other hand. Our results show that in the framework of the introduced model such a classification is not necessary, as long as the effects are job-independent. The model introduced in this paper covers most previously known models. The solution algorithms are developed within the same general framework and their running times are no worse than those available earlier for problems with less general effects.

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“…Based on the above analysis and Lemma 1, the following O(n log n) algorithm which is similar to Algorithm 1 in Kuo and Yang (2007) is provided to solve the problem 1/p ir = (p i + αt)r a /ETCP.…”

Section: The Earliness Tardiness and Due Date Penalty Minimizationmentioning

confidence: 99%

Single-machine scheduling with both deterioration and learning effects

Yang

Kuo

2009

Ann Oper Res

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This paper considers a single-machine scheduling problem with both deterioration and learning effects. The objectives are to respectively minimize the makespan, the total completion times, the sum of weighted completion times, the sum of the kth power of the job completion times, the maximum lateness, the total absolute differences in completion times and the sum of earliness, tardiness and common due-date penalties. Several polynomial time algorithms are proposed to optimally solve the problem with the above objectives.

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Single machine scheduling with past-sequence-dependent setup times and learning effects

Cited by 72 publications

References 16 publications

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

Combining time and position dependent effects on a single machine subject to rate-modifying activities

Single-machine scheduling with both deterioration and learning effects

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