Predictive heuristics to generate robust and stable schedules in single machine systems under disruptions

Abtahi, Zeinab; Sahraeian, Rashed; Rahmani, Donya

doi:10.24200/sci.2019.50809.1873

Cited by 1 publication

(2 citation statements)

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“…The DBM method employs a modified shifting bottleneck heuristics and one-machine robustness and stability optimization theorem [33]; shifting bottleneck (SB) heuristics [5] decomposes a problem into subproblems and solve each sub-problem optimally [25] using the shortest expected processing time (SEPT) first rule.…”

Section: Solution Methodsmentioning

confidence: 99%

“…Then we compare it to an exact solution method. The former (Our proposed heuristic) employs modified SB and a theorem of Abtahi et al [33], and the latter uses a theorem of Pinedo [34] to hedge against job processing time uncertainty. We employ the Right-Shifting (RS) rescheduling method to obtain a realistic schedule after machine failures occurrence.…”

Section: Literature Reviewmentioning

confidence: 99%

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Robust and Stable Flow Shop Scheduling Problem under Uncertain Processing Times and Machines’ Disruption

Abtahi

Sahraeian

2021

IJE

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This paper presents a predictive robust and stable approach for a two-machine flow shop scheduling problem with machine disruption and uncertain job processing time. Indeed, a general approach is proposed that can be used for robustness and stability optimization in an m-machine flow shop or job shop scheduling problem. The robustness measure is the total expected realized completion time. The expected sum of squared aberration between each jobs' completion time in the realized and initial schedules is the stability measure. We proposed and compared two methods to deal with such an NPhard problem; a method based on decomposing the problem into subproblem and solving each subproblem, and a theorem-based method. The extensive computational results indicated that the second method has a better performance in terms of robustness and stability, especially in large-sized problems. In other words, the second method is preferable because of the better manufacturer responsiveness to the customer and the production staff satisfaction enhancement.The expected real completion time of job j on the machine i

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Section: Solution Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%