Single-machine scheduling with a position-based learning effect and fuzzy processing times

Ahmadizar, Fardin; Hosseini, Leila

doi:10.1007/s00170-011-3190-0

Cited by 14 publications

(5 citation statements)

References 21 publications

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“…Then in a queue, the fuzzy numbers are summed up, so thatÃ +Ũ = (a 1 + u 1 , a 2 + u 2 , a 3 + u 3 ). Additionally, for comparing two TFNs, a ranking method must be employed that here the Sakawa ranking method is applied [58,59] It is noticeable that in QLE and QLE.Fuzzy, precise information about the queue length must be available, which is supposed unlikely under vagueness.…”

Section: Applied Methodsologymentioning

confidence: 99%

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Mehrsai

Karimi

Scholz‐Reiter

2012

Int J Adv Manuf Technol

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Nowadays, material planning and control strategies are becoming continuously complex tasks spanning from individual plants to logistic networks. In fact, this is the consequence of increasing intricacy in product variants and their respective convolution in networks' structures. Customers ask for specific products with individual characteristics that force companies for more clever performances by more flexibility. For doing so, the existing planning and control systems, which work based on central monitoring and controlling, show some limitations for organizing every operation on time or in the right time. Therefore, in the recent decade, a great attention is put on decentralized control and, to some extent, autonomy. This paper tries to investigate the possibility of combining this new research paradigm with existing strategies in production logistics, in order to improve material handling and control task according to material flow criteria. To show this, an exemplary plant after decoupling point out of a logistic network is considered for simulation and analysis. This combines Conwip system with learning autonomous pallets' concept in a discrete event simulation model. Several decentralized control scenarios are experimented and compared together. Here, the learn methodology is brought to pallets based on fuzzy rules and advantage of closed loop systems.

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Section: Applied Methodsologymentioning

confidence: 99%

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Mehrsai

Karimi

Scholz‐Reiter

2012

Int J Adv Manuf Technol

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“…The fuzzy approach is employed in 2.2% of the articles to model the job processing time. The single machine configuration appears in the majority of contributions [32][33][34][35], followed by the parallel machine configuration [36][37][38][39][40].…”

Section: System Configurationmentioning

confidence: 99%

Taxonomy of Scheduling Problems with Learning and Deterioration Effects

2022

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In traditional scheduling problems, job processing times are considered constant and known in advance. This assumption is, however, a simplification when it comes to hand-intensive real-life production contexts because workers usually induce variability in the job processing times due to several factors such as learning, monotony, fatigue, psychological factors, etc. These effects can decrease or increase the actual processing time when workers execute a job. The academic literature has reported several modeling and resolution approaches to deal with the phenomenon in a variety of configurations. However, there is no comprehensive review of these research outputs to the best of our knowledge. In this paper, we follow a systematic approach to review relevant contributions addressing the scheduling problem with learning and deterioration effects. Modeling approaches for learning and deterioration effects, objective functions, and solution methods employed in the literature are the main topics for the taxonomy proposed in this review. A total of 455 papers from 1999 to 2021 are included and analyzed. Different areas of interest are presented, and some opportunities for future research are identified.

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“…Fuzzy numbers, or more generally fuzzy sets of the real line, are a convenient scheme for the representation and arithmetic manipulation of ill-known quantities. 1] is called fuzzy number if the following properties hold:…”

Section: Basic Terminology Of Possibility Theorymentioning

confidence: 99%

“…Ahmadizar and Hosseini provided a polynomial time algorithm to the single machine scheduling problem with a position-based learning effect and fuzzy processing times. The solution procedure to minimize the total completion time is based on applying the shortest processing time rule to triangular fuzzy processing times [1]. The same authors proposed two polynomial time algorithms to solve the single machine scheduling problem with the position-based learning effect and fuzzy processing times when the makespan minimization is the objective function.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of optimality in the fuzzy single machine scheduling problem including discounted costs

Bentrcia

Mouss

et al. 2015

Int J Adv Manuf Technol

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The single machine scheduling problem has been often regarded as a simplified representation that contains many polynomial solvable cases. However, in real-world applications, the imprecision of data at the level of each job can be critical for the implementation of scheduling strategies. Therefore, the single machine scheduling problem with the weighted discounted sum of completion times is treated in this paper, where we assume that the processing times, weighting coefficients and discount factor are all described using trapezoidal fuzzy numbers. Our aim in this study is to elaborate adequate measures in the context of possibility theory for the assessment of the optimality of a fixed schedule. Two optimization approaches namely genetic algorithm and pattern search are proposed as computational tools for the validation of the obtained properties and results. The proposed approaches are experimented on the benchmark problem instances and a sensitivity analysis with respect to some configuration parameters is conducted. Modeling and resolution frameworks considered in this research offer promise to deal with optimality in the wide class of fuzzy scheduling problems, which is recognized to be a difficult task by both researchers and practitioners.

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Single-machine scheduling with a position-based learning effect and fuzzy processing times

Cited by 14 publications

References 21 publications

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Toward learning autonomous pallets by using fuzzy rules, applied in a Conwip system

Taxonomy of Scheduling Problems with Learning and Deterioration Effects

Evaluation of optimality in the fuzzy single machine scheduling problem including discounted costs

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