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Journal articles on the topic 'Flowshop Scheduling'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Choi, Seong Woo. "Heuristics for an m-Machine Re-Entrant Permutation Flowshop with the Objective of Total Tardiness." Applied Mechanics and Materials 752-753 (April 2015): 890–95. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.890.

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We focus on an m-machine re-entrant flowshop scheduling problem with the objective of minimizing total tardiness. In the re-entrant flowshop considered here, routes of all jobs are identical as in ordinary flowshops, but the jobs must be processed multiple times on the machines. We present heuristic algorithms, which are modified from well-known existing algorithms for the general m-machine flowshop problem or newly developed in this paper. For evaluation of the performance of the algorithms, computational experiments are performed on randomly generated test problems and results are reported.

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2

Rossi, Andrea, and Michele Lanzetta. "Nonpermutation flow line scheduling by ant colony optimization." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 27, no. 4 (June 19, 2013): 349–57. http://dx.doi.org/10.1017/s0890060413000176.

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AbstractA flow line is a conventional manufacturing system where all jobs must be processed on all machines with the same operation sequence. Line buffers allow nonpermutation flowshop scheduling and job sequences to be changed on different machines. A mixed-integer linear programming model for nonpermutation flowshop scheduling and the buffer requirement along with manufacturing implication is proposed. Ant colony optimization based heuristic is evaluated against Taillard's (1993) well-known flowshop benchmark instances, with 20 to 500 jobs to be processed on 5 to 20 machines (stages). Computation experiments show that the proposed algorithm is incumbent to the state-of-the-art ant colony optimization for flowshop with higher job to machine ratios, using the makespan as the optimization criterion.

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3

Allahverdi, Ali, Tariq Aldowaisan, and Yuri N. Sotskov. "Two-machine flowshop scheduling problem to minimize makespan or total completion time with random and bounded setup times." International Journal of Mathematics and Mathematical Sciences 2003, no. 39 (2003): 2475–86. http://dx.doi.org/10.1155/s016117120321019x.

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This paper addresses the two-machine flowshop scheduling problem with separate setup times to minimize makespan or total completion time (TCT). Setup times are relaxed to be random variables rather than deterministic as commonly used in the OR literature. Moreover, distribution-free setup times are used where only the lower and upper bounds are given. Global and local dominance relations are developed for the considered flowshops and an illustrative numerical example is given.

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4

Frostig, E., and I. Adiri. "Stochastic flowshop no-wait scheduling." Journal of Applied Probability 22, no. 1 (March 1985): 240–46. http://dx.doi.org/10.2307/3213765.

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This paper deals with special cases of stochastic flowshop, no-wait, scheduling. n jobs have to be processed by m machines . The processing time of job Ji on machine Mj is an independent random variable Ti. It is possible to sequence the jobs so that , . At time 0 the realizations of the random variables Ti, (i are known. For m (m ≧ 2) machines it is proved that a special SEPT–LEPT sequence minimizes the expected schedule length; for two (m = 2) machines it is proved that the SEPT sequence minimizes the expected sum of completion times.

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5

Frostig, E., and I. Adiri. "Stochastic flowshop no-wait scheduling." Journal of Applied Probability 22, no. 01 (March 1985): 240–46. http://dx.doi.org/10.1017/s0021900200029181.

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This paper deals with special cases of stochastic flowshop, no-wait, scheduling. n jobs have to be processed by m machines . The processing time of job Ji on machine Mj is an independent random variable Ti . It is possible to sequence the jobs so that , . At time 0 the realizations of the random variables Ti , ( i are known. For m (m ≧ 2) machines it is proved that a special SEPT–LEPT sequence minimizes the expected schedule length; for two (m = 2) machines it is proved that the SEPT sequence minimizes the expected sum of completion times.

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6

Ho, Johnny C., and Jatinder N. D. Gupta. "Flowshop scheduling with dominant machines." Computers & Operations Research 22, no. 2 (February 1995): 237–46. http://dx.doi.org/10.1016/0305-0548(94)e0007-t.

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7

Randhawa, Sabah U., Cynthia Juwono, and Sheikh Burhanuddin. "Scheduling in Multistage Flowshop Systems." Industrial Management & Data Systems 94, no. 5 (June 1994): 16–24. http://dx.doi.org/10.1108/02635579410063270.

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8

Bernstein, M. "Finding heuristics for flowshop scheduling." ACM SIGART Bulletin, no. 99 (January 1987): 32–33. http://dx.doi.org/10.1145/24667.24670.

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9

Eren, Tamer, and Ertan Güner. "The tricriteria flowshop scheduling problem." International Journal of Advanced Manufacturing Technology 36, no. 11-12 (February 16, 2007): 1210–20. http://dx.doi.org/10.1007/s00170-007-0931-1.

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10

Cheng, Chen-Yang, Shih-Wei Lin, Pourya Pourhejazy, Kuo-Ching Ying, and Yu-Zhe Lin. "No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework." Mathematics 9, no. 12 (June 9, 2021): 1335. http://dx.doi.org/10.3390/math9121335.

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Production environment in modern industries, like integrated circuits manufacturing, fiberglass processing, steelmaking, and ceramic frit, is characterized by zero idle-time between inbound and outbound jobs on every machine; this technical requirement improves energy efficiency, hence, has implications for cleaner production in other production situations. An exhaustive review of literature is first conducted to shed light on the development of no-idle flowshops. Considering the intractable nature of the problem, this research also develops an extended solution method for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP). Extensive numerical tests and statistical analysis are conducted to evaluate the developed method, comparing it with the best-performing algorithm developed to solve the BNIPFSP. Overall, the proposed extension outperforms in terms of solution quality at the expense of a longer computational time. This research is concluded by providing suggestions for the future development of this understudied scheduling extension.

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11

Lebbar, Ghita, Abdellah El Barkany, and Abdelouahhab Jabri. "Scheduling Problems of Flexible Manufacturing Systems: Review, Classification and Opportunities." International Journal of Engineering Research in Africa 26 (October 2016): 142–60. http://dx.doi.org/10.4028/www.scientific.net/jera.26.142.

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This paper will relate initially to the scheduling characteristics of flexible manufacturing systems, and more specifically, the scheduling problems in flowshop and hybrid flowshop type systems representing interesting structures for the modeling of several problems resulting from the industrial world. Subsequently, we will focus our attention on the principal methods for solving scheduling problems, while presenting in the following the main published works for the aforementioned systems. Lastly, a comparative analysis will be carried out to highlight the fundamental ideas leading to the adoption of an effective approach capable of producing an optimal solution in a reasonable calculation time.

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12

HU, XIAOFENG, JINGSONG BAO, and YE JIN. "A TABU SEARCH ALGORITHM FOR A PIPE-PROCESSING FLOWSHOP SCHEDULING PROBLEM MINIMIZING TOTAL TARDINESS IN A SHIPYARD." Asia-Pacific Journal of Operational Research 26, no. 06 (December 2009): 817–29. http://dx.doi.org/10.1142/s0217595909002493.

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This paper focuses on scheduling problem of a pipe-processing flowshop in a shipyard. The flowshop composes of five stages, including cutting, bending, welding preprocessing, argon-welding and CO 2-welding, and each stage consists of identical parallel machines. Since thousands of pipes are mounted on the hull block before erection, the pipe-processing scheduling is a critical task for shipbuilding to meet the due date of the block erection. A tabu search algorithm is developed for the scheduling problem with the objective of minimizing total tardiness. Computational experiments are performed on the collected real data. Results show that the proposed algorithm is efficient for this problem.

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13

CELANO, G., A. COSTA, and S. FICHERA. "AN EVOLUTIONARY ALGORITHM FOR PURE FUZZY FLOWSHOP SCHEDULING PROBLEMS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, no. 06 (December 2003): 655–69. http://dx.doi.org/10.1142/s0218488503002466.

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The pure flowshop scheduling problem is here investigated from a perspective considering me uncertainty associated with the execution of shop floor activities. Being the flowshop problem is NP complete, a large number of heuristic algorithms have been proposed in literature to determine an optimal solution. Unfortunately, these algorithms usually assume a simplifying hypothesis: the problem data are assumed as deterministic, i.e. job processing times and the due dates are expressed through a unique value, which does not reflect the real process variability. For this reason, some authors have recently proposed the use of a fuzzy set theory to model the uncertainty in scheduling problems. In this paper, a proper genetic algorithm has been developed for solving the fuzzy flowshop scheduling problem. The optimisation involves two different objectives: the completion time minimisation and the due date fulfilment; both the single and multi-objective configurations have been considered. A new ranking criterion has been proposed and its performance has been tested through a set of test problems. A numerical analysis confirms the efficiency of the proposed optimisation procedure.

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14

Terekhov, D., T. T. Tran, D. G. Down, and J. C. Beck. "Integrating Queueing Theory and Scheduling for Dynamic Scheduling Problems." Journal of Artificial Intelligence Research 50 (July 22, 2014): 535–72. http://dx.doi.org/10.1613/jair.4278.

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Dynamic scheduling problems consist of both challenging combinatorics, as found in classical scheduling problems, and stochastics due to uncertainty about the arrival times, resource requirements, and processing times of jobs. To address these two challenges, we investigate the integration of queueing theory and scheduling. The former reasons about long-run stochastic system characteristics, whereas the latter typically deals with short-term combinatorics. We investigate two simple problems to isolate the core differences and potential synergies between the two approaches: a two-machine dynamic flowshop and a flexible queueing network. We show for the first time that stability, a fundamental characteristic in queueing theory, can be applied to approaches that periodically solve combinatorial scheduling problems. We empirically demonstrate that for a dynamic flowshop, the use of combinatorial reasoning has little impact on schedule quality beyond queueing approaches. In contrast, for the more complicated flexible queueing network, a novel algorithm that combines long-term guidance from queueing theory with short-term combinatorial decision making outperforms all other tested approaches. To our knowledge, this is the first time that such a hybrid of queueing theory and scheduling techniques has been proposed and evaluated.

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15

Bahari, M. Faudzi, Sudrajat Sudrajat, and E. Lesmana. "Minimize Rental Costs on Flowshop Scheduling." JURNAL ILMIAH SAINS 20, no. 2 (May 25, 2020): 58. http://dx.doi.org/10.35799/jis.20.2.2020.27765.

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ABSTRACTThis paper discusses solving the problem of rental costs in a Flowshop scheduling with n-jobs and m-Machines in small and medium-sized companies to minimize rental costs to be paid. The proposed method is the development of an existing method using several proven propositions. The method used is applied in a sandals company that rents 11 machines used to produce 6 types of products. The proposed method yields a rental fee of IDR 1,071,121.5.Keywords: Flow shop; minimize rental cost; scheduling Minimisasi Biaya Sewa pada Penjadwalan FlowshopABSTRAKPaper ini membahas mengenai minimisasi biaya sewa yang harus dibayar oleh perusahaan berskala kecil-menengah yang menggunakan penjadwalan flowshop dengan n-buah pekerjaan yang dikerjakan oleh m-buah mesin pada proses produksinya. Metode yang dibuat adalah pengembangan dari metode sebelumnya yang dibuktikan dengan menggunakan beberapa proposisi pendukung. Metode ini telah diaplikasikan pada sebuah perusahaan sandal yang memproduksi 6 jenis sandal dengan menggunakan 11 mesin yang berbeda. Berdasarkan metode ini perusahaan harus membayar biaya sewa mesin sebesar Rp. 1,071,121.5.Kata Kunci: Flow shop; minimisasi biaya sewa; penjadwalan

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16

Gupta, Jatinder N. D. "Two-Stage, Hybrid Flowshop Scheduling Problem." Journal of the Operational Research Society 39, no. 4 (April 1988): 359. http://dx.doi.org/10.2307/2582115.

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17

ISHIBUCHI, Hisao, Tadahiko MURATA, and Shigemitsu TOMIOKA. "Flowshop Scheduling by Genetic Local Search." Transactions of the Institute of Systems, Control and Information Engineers 10, no. 10 (1997): 563–65. http://dx.doi.org/10.5687/iscie.10.563.

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18

Čepek, Ondřej, Masanori Okada, and Milan Vlach. "Nonpreemptive flowshop scheduling with machine dominance." European Journal of Operational Research 139, no. 2 (June 2002): 245–61. http://dx.doi.org/10.1016/s0377-2217(01)00356-3.

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19

Koulamas, Christos, and George J. Kyparisis. "Concurrent flowshop scheduling to minimize makespan." European Journal of Operational Research 156, no. 2 (July 2004): 524–29. http://dx.doi.org/10.1016/s0377-2217(03)00142-5.

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20

Haouari, Mohamed, and Lotfi Hidri. "On the hybrid flowshop scheduling problem." International Journal of Production Economics 113, no. 1 (May 2008): 495–97. http://dx.doi.org/10.1016/j.ijpe.2007.10.007.

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21

Allahverdi, A., and M. Savsar. "Stochastic proportionate flowshop scheduling with setups." Computers & Industrial Engineering 39, no. 3-4 (April 2001): 357–69. http://dx.doi.org/10.1016/s0360-8352(01)00011-0.

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22

Yang, Dar-Li, and Maw-Sheng Chern. "Two-machine flowshop group scheduling problem." Computers & Operations Research 27, no. 10 (September 2000): 975–85. http://dx.doi.org/10.1016/s0305-0548(99)00070-2.

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23

Almasarwah, Najat, and Gürsel Süer. "Product Scheduling in a Flowshop Cell." Procedia Manufacturing 17 (2018): 206–13. http://dx.doi.org/10.1016/j.promfg.2018.10.038.

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24

Gupta, Jatinder N. D. "Two-Stage, Hybrid Flowshop Scheduling Problem." Journal of the Operational Research Society 39, no. 4 (April 1988): 359–64. http://dx.doi.org/10.1057/jors.1988.63.

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25

Cao, Dong, and Mingyuan Chen. "Parallel flowshop scheduling using Tabu search." International Journal of Production Research 41, no. 13 (January 2003): 3059–73. http://dx.doi.org/10.1080/0020754031000106443.

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26

Oladeinde, MH, AI Momodu, and CA Oladeinde. "Flowshop Scheduling Using a Network Approach." Nigerian Journal of Technology 34, no. 2 (March 31, 2015): 286. http://dx.doi.org/10.4314/njt.v34i2.11.

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27

Dudek, R. A., S. S. Panwalkar, and M. L. Smith. "The Lessons of Flowshop Scheduling Research." Operations Research 40, no. 1 (February 1992): 7–13. http://dx.doi.org/10.1287/opre.40.1.7.

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28

Gupta, Jatinder N. D., Arindam Majumder, and Dipak Laha. "Flowshop scheduling with artificial neural networks." Journal of the Operational Research Society 71, no. 10 (June 24, 2019): 1619–37. http://dx.doi.org/10.1080/01605682.2019.1621220.

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29

Lin, B. M. T., and T. C. E. Cheng. "Two-Machine Flowshop Batching and Scheduling." Annals of Operations Research 133, no. 1-4 (January 2005): 149–61. http://dx.doi.org/10.1007/s10479-004-5029-7.

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30

Murata, Tadahiko, Hisao Ishibuchi, and Hideo Tanaka. "Genetic algorithms for flowshop scheduling problems." Computers & Industrial Engineering 30, no. 4 (September 1996): 1061–71. http://dx.doi.org/10.1016/0360-8352(96)00053-8.

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31

Fan, B. Q., and T. C. E. Cheng. "Two-agent scheduling in a flowshop." European Journal of Operational Research 252, no. 2 (July 2016): 376–84. http://dx.doi.org/10.1016/j.ejor.2016.01.009.

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32

Naderi, B., and Rubén Ruiz. "The distributed permutation flowshop scheduling problem." Computers & Operations Research 37, no. 4 (April 2010): 754–68. http://dx.doi.org/10.1016/j.cor.2009.06.019.

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33

Gruzlikov, A. M., N. V. Kolesov, Iu M. Skorodumov, and M. V. Tolmacheva. "Using solvable classes in flowshop scheduling." International Journal of Advanced Manufacturing Technology 88, no. 5-8 (May 16, 2016): 1535–46. http://dx.doi.org/10.1007/s00170-016-8828-5.

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34

Gupta, Jatinder N. D., and Edward F. Stafford. "Flowshop scheduling research after five decades." European Journal of Operational Research 169, no. 3 (March 2006): 699–711. http://dx.doi.org/10.1016/j.ejor.2005.02.001.

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35

Zhong, Weiya, and Zhi-Long Chen. "Flowshop scheduling with interstage job transportation." Journal of Scheduling 18, no. 4 (November 25, 2014): 411–22. http://dx.doi.org/10.1007/s10951-014-0409-6.

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36

Behnamian, J., and S. M. T. Fatemi Ghomi. "Multi-objective fuzzy multiprocessor flowshop scheduling." Applied Soft Computing 21 (August 2014): 139–48. http://dx.doi.org/10.1016/j.asoc.2014.03.031.

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37

Gharbi, Anis, Mohamed Labidi, and Mohamed Aly Louly. "The Nonpermutation Flowshop Scheduling Problem: Adjustment and Bounding Procedures." Journal of Applied Mathematics 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/273567.

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We consider the makespan minimization in a flowshop environment where the job sequence does not have to be the same for all the machines. Contrarily to the classical permutation flowshop scheduling problem, this strongly NP-hard problem received very scant attention in the literature. In this paper, some improved single-machine-based adjustment procedures are proposed, and a new two-machine-based one is introduced. Based on these adjustments, new lower and upper bounding schemes are derived. Our experimental analysis shows that the proposed procedures provide promising results.

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38

Tang, Dan, and Hong Ping Shu. "A Heuristic Algorithm for Flowshop Scheduling Problem." Advanced Materials Research 591-593 (November 2012): 626–30. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.626.

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Flow Shop Scheduling Problem is a class of scheduling problems with a work shop in which the flow control shall enable an appropriate sequencing for each job and for processing on a set of machines in compliance with given processing orders. In this paper, we propose a new heuristic algorithm based on the analysis and research of which problem, the new method introducing a evaluate mechanism of the relative position of any two jobs to the completion time, and the efficiency and performance has been improved .The result of simulation experiments shows that, our new heuristic algorithm has good performance, and the average quality and stability of scheduling sequences generated by new method is significantly better than other heuristic algorithm which has the same complexity.

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39

Cao, Ying, Hua Xuan, and Jing Liu. "Dynamic Hybrid Flowshop Scheduling with Batching Production." Applied Mechanics and Materials 65 (June 2011): 562–67. http://dx.doi.org/10.4028/www.scientific.net/amm.65.562.

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Based on the background of steel-tube production, this paper presents the dynamic hybrid flowshop scheduling with batching scheduling at the first stage, and establishes an integer programming model for this problem. The objective is to minimize the total weighted completion time. The Lagrangian relaxation algorithm is constructed to slove the above model where dynamic programming is presented to solve batch-level subproblems, and a two-stage heuristic is presented to construct a feasible schedule. Testing results on small to medium problem sizes show that this method can obtain satisfactory quality solution in a shorter computation time.

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40

Xuan, Hua. "Hybrid Flowshop Scheduling with Finite Transportation Capacity." Applied Mechanics and Materials 65 (June 2011): 574–78. http://dx.doi.org/10.4028/www.scientific.net/amm.65.574.

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This paper studies a class of hybrid flowshop scheduling problem characterized by release time, transportation time and transportation capacity of one unit for each transporter. This problem is formulated as an integer programming model and a Lagrangian relaxation algorithm is designed to solve it. Testing results on problems of small to medium sizes show that the Lagrangian relaxation algorithm can obtain an acceptable near optimal schedule within a shorter CPU time.

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41

Narain, Laxmi, and P. C. Bagga. "Flowshop/no-idle scheduling to minimise the mean flowtime." ANZIAM Journal 47, no. 2 (October 2005): 265–75. http://dx.doi.org/10.1017/s1446181100010026.

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AbstractThis paper deals with n-job, 2-machine flowshop/mean flowtime scheduling problems working under a “no-idle” constraint, that is, when machines work continuously without idle intervals. A branch and bound technique has been developed to solve the problem.

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42

Liao, C. J., W. C. Yu, and C. B. Joe. "Bicriterion Scheduling in the Two-Machine Flowshop." Journal of the Operational Research Society 48, no. 9 (September 1997): 929. http://dx.doi.org/10.2307/3010492.

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43

Rajendran, Chandrasekharan. "Two-Stage Flowshop Scheduling Problem with Bicriteria." Journal of the Operational Research Society 43, no. 9 (September 1992): 871. http://dx.doi.org/10.2307/2583288.

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44

Sadjadi, S. J., M. B. Aryanezhad, and Mohsen Ziaee. "The General Flowshop Scheduling Problem: Mathematical Models." Journal of Applied Sciences 8, no. 17 (August 15, 2008): 3032–37. http://dx.doi.org/10.3923/jas.2008.3032.3037.

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45

Lee, Chung-Yee. "Two-machine flowshop scheduling with availability constraints." European Journal of Operational Research 114, no. 2 (April 1999): 420–29. http://dx.doi.org/10.1016/s0377-2217(97)00452-9.

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46

ZHANG, Chang-Sheng, Ji-Gui SUN, Qing-Yun YANG, and Li-Hui ZHENG. "A Hybrid Algorithm for Flowshop Scheduling Problem." Acta Automatica Sinica 35, no. 3 (May 31, 2009): 332–36. http://dx.doi.org/10.3724/sp.j.1004.2009.00332.

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47

Chou, Fuh-Der, and Ching-En Lee. "Two-machine flowshop scheduling with bicriteria problem." Computers & Industrial Engineering 36, no. 3 (July 1999): 549–64. http://dx.doi.org/10.1016/s0360-8352(99)00149-7.

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48

Koulamas, Christos, and George J. Kyparisis. "The three-stage assembly flowshop scheduling problem." Computers & Operations Research 28, no. 7 (June 2001): 689–704. http://dx.doi.org/10.1016/s0305-0548(00)00004-6.

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49

Rajendran, Chandrasekharan. "Two-Stage Flowshop Scheduling Problem with Bicriteria." Journal of the Operational Research Society 43, no. 9 (December 1993): 871–84. http://dx.doi.org/10.1057/jors.1992.126.

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50

Yang, W. H. "Group scheduling in a two-stage flowshop." Journal of the Operational Research Society 53, no. 12 (December 2002): 1367–73. http://dx.doi.org/10.1057/palgrave.jors.2601454.

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