A note: flowshop scheduling with linear deterioration and job-rejection

Mor, Baruch; Mosheiov, Gur

doi:10.1007/s10288-020-00436-z

Cited by 12 publications

(1 citation statement)

References 34 publications

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“…This occurs at any time after pre-processing (Demir & Previtali, 2017), causing a longer processing time when the process begins at a later time (Cheng, Kang & Ng, 2004). A linear deterioration, i.e., the increase of part processing time at a constant proportion δ of the initial processing time, was assumed in this research (Mor & Mosheiov, 2021), leading to deterioration function D(x) in Equation ( 12), ( 12) where t = initial processing time (before deterioration), x = part sequence, and δ = deterioration rate of 0 or more (a higher δ means a faster deterioration, δ = 0 means no deterioration).…”

Section: Time-changing Effectsmentioning

confidence: 99%

A flow shop batch scheduling model with pre-processing and time-changing effects to minimize total actual flow time

Kurniawan,

Yusriski,

Isnaini

et al. 2024

JIEM

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Purpose: This paper investigates a batch scheduling problem where pre-processing is required for parts before processing, considering time-changing effects from part deterioration and operator learning-forgetting.Design/methodology/approach: A mathematical model was developed with the decision variables of the number of batches, the number of pre-processings, batch sizes, and the schedule of processes and pre-processings to minimize total actual flow time. Different numbers of batches were gradually tried and increased until the objective function stopped improving. The minimum number of pre-processings that resulted in a feasible solution was examined at each number of batches.Findings: Our experiment showed that: (1) A faster operator learning led to a lower optimal number of batches and a lower total actual flow time, (2) A faster part deterioration brought a higher number of batches and a higher total actual flow time, (3) The model minimized the number of pre-processings by only scheduling pre-processings before the operations at machine 1, and (4) The model divided the parts into small batches to prevent increased processing time due to part deterioration.Research limitations: The research did not consider multi-due date and multi-item system which require pre-processings with different times and capacities.Practical implications: Production managers should assign fast learning operators to shorter batches and faster deteriorating parts.Originality/value: This research was the first to consider pre-processing in batch scheduling.

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Section: Time-changing Effectsmentioning

confidence: 99%