Two-machine flow shop scheduling problem with blocking, multi-task flexibility of the first machine, and preemption

Khorasanian, Danial; Moslehi, Ghasem

doi:10.1016/j.cor.2016.09.023

Cited by 12 publications

(5 citation statements)

References 41 publications

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“…Each job must be performed at distinct rates by one machine. Khorasanian and Moslehi [55] investigated the two-machine flow shop scheduling problem with blocking. Another factor was the first machine's preemption, multi-task flexibility, and makespan minimization as a criterion.…”

Section: Research Results and Recommendations On C Max For F 2/fmentioning

confidence: 99%

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

2021

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Flow shop scheduling is a type of scheduling where sequence follows for each job on a set of machines for processing. In practice, jobs in flow shops can arrive at irregular times, and the no-wait constraint allows the changes in the job order to flexibly manage such irregularity. The flexible flow shop scheduling problems with no-wait have mainly addressed for flow optimization on the shop floor in manufacturing, processing, and allied industries. The scope of this paper is to identify the literature available on permutation and non-permutation flow shop scheduling with no-wait constraint. This paper organizes scheduling problems based on performance measures of variability and shop environments. The extended summary of two/three-machine and m-machine problems has been compiled, including their objectives, algorithms, parametric considerations, and their findings. A systematic appearance of both conceptual and analytical results summarizes various advances of the no-wait constraint. The paper includes independently investigated problems and suggestions for future research directions.

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Section: Research Results and Recommendations On C Max For F 2/fmentioning

confidence: 99%

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

2021

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“…Therefore, a total number of 120 instances were produced. For more recent studies of Taillard's instances we refer the interested reader to Khatami and Zegordi (2017); Khorasanian and Moslehi (2017) and Liu et al (2017). Vallada et al (2015) carried out extensive experiments and selected 240 "small" instances and 240 "large" instances, from a pool of 72,000 instances.…”

Section: Instance Generation and Evaluationmentioning

confidence: 99%

Makespan minimization for the m-machine ordered flow shop scheduling problem

Khatami

Salehipour

Hwang

2019

Computers & Operations Research

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“…Tabel ini menunjukkan lama pengerjaan setiap tahap pada suatu projek dalam satuan minggu. (McConnell, 2006).…”

Section: Data Penelitian Projekunclassified

“…Dalam flow-shop scheduling problem, terdapat sejumlah n job dan m mesin, dimana setiap job harus diproses pada setiap mesin mulai dari mesin 1 sampai mesin m secara berurutan. Dengan kondisi seperti ini, tentunya akan muncul buffer dengan kapasitas yang tidak terbatas diantara mesin (Khorasanian, 2017). Pada permasalahan FSP ini, dapat diartikan dengan bagaimana membuat urutan pekerjaan, sehingga waktu yang dibutuhkan untuk menyelesaikan semua pekerjaan dapat diminimalkan.…”

Section: Flow-shop Problemunclassified

Optimasi Penjadwalan Pengerjaan Software Pada Software House Dengan Flow-Shop Problem Menggunakan Artificial Bee Colony

Fhadli

Jauhari

Prabowo

et al. 2016

JTIIK

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AbstrakPenelitian ini mengusulkan sebuah implementasi terkait optimasi penjadwalan pengerjaan software pada software house dengan Flow-Shop Problem (FSP) menggunakan algoritma Artificial Bee Colony (ABC). Dimana dalam FSP dibutuhkan suatu solusi untuk menyelesaikan suatu job/task dengan meminimalkan total cost yang dikeluarkan. Terdapat constraint yang perlu diperhatikan dalam objek permasalahan penelitian ini, yaitu lama waktu penyelesaian keseluruhan projek software yang tidak pasti. Dalam penelitian ini akan disusun sebuah representasi solusi yaitu berupa urutan pengerjaan projek dengan total waktu pengerjaan yang minimum. Pengujian akan dilakukan dengan tiga kali percobaan untuk setiap kondisi uji coba, yaitu uji coba batas parameter iterasi dan uji coba batas parameter limit. Dari hasil pengujian didapatkan bahwa penggunaan algoritma yang dibahas dalam penelitian ini bisa mengurangi waktu pengerjaan jika jumlah iterasi dan jumlah colony diperbesar.Kata kunci: optimasi, flow-shop problem, artificial bee colony, swarm intelligence, meta-heuristik. AbstractThis research proposed an implementation related to software execution scheduling process at a software house with Flow-Shop Problem (FSP) using Artificial Bee Colony (ABC) algorithm. Which in FSP required a solution to complete some job/task along with its overall cost at a minimum. There is a constraint that should be kept to note in this research, that is the uncertainty completion time of its jobs. In this research, we will present a solution that is a sequence order of project execution with its overall completion time at a minimum. An experiment will be performed with 3 attempts on each experiment conditions, that is an experiment of iteration parameter and experiment of limit parameter. From this experiment, we concluded that the use of this algorithm explained in this paper can reduce project execution time if we increase the value of total iteration and total colony.

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Two-machine flow shop scheduling problem with blocking, multi-task flexibility of the first machine, and preemption

Cited by 12 publications

References 41 publications

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

Multi-objective permutation and non-permutation flow shop scheduling problems with no-wait: a systematic literature review

Makespan minimization for the m-machine ordered flow shop scheduling problem

Optimasi Penjadwalan Pengerjaan Software Pada Software House Dengan Flow-Shop Problem Menggunakan Artificial Bee Colony

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