Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times

Mönch, Lars; Balasubramanian, Hari; Fowler, John W.; Pfund, Michele E.

doi:10.1016/j.cor.2004.04.001

Cited by 178 publications

(87 citation statements)

References 23 publications

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“…According to their DBDH method, all alternative batches of a product type in the selected time-window are composed and prioritized, and wait and start decisions are made accordingly. Mönch, Balasubramanian, Fowler, and Pfund (2005) proposed three different versions of time-window based priority indexing for the problem with different ready times. They also discuss the use of decision theory in prioritizing batches.…”

Section: Batch Control From the Consumer's Perspectivementioning

confidence: 99%

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

Cerekci

Banerjee

2015

Computers & Industrial Engineering

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Section: Batch Control From the Consumer's Perspectivementioning

confidence: 99%

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

Cerekci

Banerjee

2015

Computers & Industrial Engineering

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“…Oulamara et al [37] have studied a two processor problem that involved a discrete and batch processor. Mönch et al [32] investigated two different approaches for scheduling jobs with incompatible job families and unequal ready times on parallel batch processors and developed genetic algorithms to minimize the total weighted tardiness criterion.…”

Section: Related Literaturementioning

confidence: 99%

Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

Noroozi

Mokhtari

2014

Neural Comput & Applic

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The complexity of printed circuit boards (PCBs), as an important sector of the electronics manufacturing industry, has increased over the last three decades. This paper focuses on a practical application observed at a PCB assembly line of electronics manufacturing facility. It is shown that this problem is equivalent to a flowshop scheduling with multiple heterogeneous batch processors where processors can perform multiple tasks as long as the sizes of jobs in a batch do not violate the processors' capacity. The equivalent problem is mathematically formulated as a mixed integer programming model. Then, a Monte Carlo simulation is incorporated into high-level genetic algorithm-based intelligent optimization techniques to assess the performance of makespan-oriented system under uncertain processing times. At each iteration of algorithm, the output of simulator is used by optimizers to provide online feedbacks on the progress of the search and direct the search toward a promising solution zone. Furthermore, various parameters and operators of the algorithm are discussed and calibrated by means of Taguchi statistical technique. The result of extensive computational experiments shows that the solution approach gives high-quality solutions in reasonable computational time.

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“…Mönch ve diğ. [9], eşit işlem süresine sahip işlerin bir iş ailesi oluşturduğu farklı büyüklükteki ve farklı hazırlık zamanlarına sahip işlerin yığın üretim yapan eş özellikteki birden çok makinede çizelgeleme problemi ile ilgilenmiştir. Amaç, işlere ait gecikmelerin ağırlıklı toplamını (∑ ) en küçüklemektir.…”

Section: Yazın Taramasıunclassified

Job allocation and scheduling of batch processing ovens: An integer programming model

Edis¹,

Kuru²

2017

Pamukkale J Eng Sci

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Heuristic scheduling of jobs on parallel batch machines with incompatible job families and unequal ready times

Cited by 178 publications

References 23 publications

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

Scheduling of printed circuit board (PCB) assembly systems with heterogeneous processors using simulation-based intelligent optimization methods

Job allocation and scheduling of batch processing ovens: An integer programming model

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