Tariq Aldowaisan, Ali Allahverdi

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Department of Industrial and Management Systems Engineering, Kuwait University, Kuwait City, Kuwait.
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Abstract: The m-machine no-wait flowshop scheduling problem is addressed where setup times are treated as separate from processing times. The objective is to minimize total tardiness. Different dispatching rules have been investigated and three were found to be superior. Two heuristics, a simulated annealing (SA) and a genetic algorithm (GA), have been proposed by using the best performing dispatching rule as the initial solution for SA, and the three superior dispatching rules as part of the initial population for GA. Moreover, improved versions of SA and GA are proposed using an insertion algorithm. Extensive computational experiments reveal that the improved versions of SA and GA perform about 95% better than SA and GA. The improved version of GA outperforms the improved version of SA by about 3.5%.

Keywords: No-Wait Flowshop, Scheduling, Setup Times, Total Tardiness, Simulated Annealing, Genetic Algorithm

Cite this paper: Aldowaisan, T. and Allahverdi, A. (2015) No-Wait Flowshops to Minimize Total Tardiness with Setup Times. Intelligent Control and Automation, 6, 38-44. doi: 10.4236/ica.2015.61005.

References

[1]   Hall, N.G. and Sriskandarajah, C. (1996) A Survey of Machine Scheduling Problems with Blocking and No-Wait in Process. Operations Research, 44, 510-525. http://dx.doi.org/10.1287/opre.44.3.510

[2]   Aldowaisan, T. and Allahverdi, A. (2003) New Heuristics for No-Wait Flowshops to Minimize Makespan. Computers & Operations Research, 30, 1219-1231.
http://dx.doi.org/10.1016/S0305-0548(02)00068-0

[3]   Allahverdi, A. and Aldowaisan, T. (2004) No-Wait Flowshops with Bicriteria of Makespan and Maximum Lateness. European Journal of Operational Research, 152, 132-147.
http://dx.doi.org/10.1016/S0377-2217(02)00646-X

[4]   Framinan, J.M. and Nagano, M.S. (2008) Evaluating the Performance for Makespan Minimisation in No-Wait Flowshop Sequencing. Journal of Materials Processing Technology, 197, 1-9.
http://dx.doi.org/10.1016/j.jmatprotec.2007.07.039

[5]   Pan, Q.K., Fatih Tasgetiren, M. and Liang, Y.C. (2008) A Discrete Particle Swarm Optimization Algorithm for the No-Wait Flowshop Scheduling Problem. Computers & Operations Research, 35, 2807-2839. http://dx.doi.org/10.1016/j.cor.2006.12.030

[6]   Kalczynski, P.J. and Kamburowski, J. (2007) On No-Wait and No-Idle Flow Shops with Makespan Criterion. European Journal of Operational Research, 178, 677-685.
http://dx.doi.org/10.1016/j.ejor.2006.01.036

[7]   Davendra, D., Zelinka, I., Bialic-Davendra, M., Senkerik, R. and Jasek, R. (2013) Discrete Self-Organising Migrating Algorithm for Flow-Shop Scheduling with No-Wait Makespan. Mathematical and Computer Modelling, 57, 100-110. http://dx.doi.org/10.1016/j.mcm.2011.05.029

[8]   Zhu, J., Li, X. and Wang, Q. (2009) Complete Local Search with Limited Memory Algorithm for No-Wait Job Shops to Minimize Makespan. European Journal of Operational Research, 198, 378-386.
http://dx.doi.org/10.1016/j.ejor.2008.09.015

[9]   Tseng, L.Y. and Lin, Y.T. (2010) A Hybrid Genetic Algorithm for No-Wait Flowshop Scheduling Problem. International Journal of Production Economics, 128, 144-152.
http://dx.doi.org/10.1016/j.ijpe.2010.06.006

[10]   Nagano, M.S., Da Silva, A.A. and Nogueira Lorena, L.A. (2014) An Evolutionary Clustering Search for the No-Wait Flow Shop Problem with Sequence Dependent Setup Times. Expert Systems with Applications, 41, 3628-3633. http://dx.doi.org/10.1016/j.eswa.2013.12.013

[11]   Chen, C.L., Neppalli, R.V. and Aljaber, N. (1996) Genetic Algorithms Applied to the Continuous Flow Shop Problem. Computers & Industrial Engineering, 30, 919-929.
http://dx.doi.org/10.1016/0360-8352(96)00042-3

[12]   Aldowaisan, T. and Allahverdi, A. (2004) New Heuristics for m-Machine No-Wait Flowshop to Minimize Total Completion Time. Omega, 32, 345-352. http://dx.doi.org/10.1016/j.omega.2004.01.004

[13]   Chang, J.L., Gong, D.W. and Ma, X.P. (2007) A Heuristic Genetic Algorithm for No-Wait Flowshop Scheduling Problem. Journal of China University of Mining and Technology, 17, 582-586.
http://dx.doi.org/10.1016/S1006-1266(07)60150-3

[14]   Nagano, M.S., Miyata, H.H. and Araújo, D.C. (2014) A Constructive Heuristic for Total Flowtime Minimization in a No-Wait Flowshop with Sequence-Dependent Setup Times. Journal of Manufacturing Systems. http://dx.doi.org/10.1016/j.jmsy.2014.06.007

[15]   Aldowaisan, T.A. and Allahverdi, A. (2012) No-Wait Flowshop Scheduling Problem to Minimize the Number of Tardy Jobs. The International Journal of Advanced Manufacturing Technology, 61, 311-323. http://dx.doi.org/10.1007/s00170-011-3659-x

[16]   Jolai, F., Asefi, H., Rabiee, M. and Ramezani, P. (2013) Bi-Objective Simulated Annealing Approaches for No-Wait Two-Stage Flexible Flow Shop Scheduling Problem. Scientia Iranica, 20, 861-872.

[17]   Liu, G., Song, S. and Wu, C. (2013) Some Heuristics for No-Wait Flowshops with Total Tardiness Criterion. Computers & Operations Research, 40, 521-525.
http://dx.doi.org/10.1016/j.cor.2012.07.019

[18]   Aldowaisan, T. and Allahverdi, A. (2012) Minimizing Total Tardiness in No-Wait Flowshops. Foundations of Computing and Decision Sciences, 37, 149-162.
http://dx.doi.org/10.2478/v10209-011-0009-6

[19]   Allahverdi, A. and Soroush, H.M. (2008) The Significance of Reducing Setup Times/Setup Costs. European Journal of Operational Research, 187, 978-984.
http://dx.doi.org/10.1016/j.ejor.2006.09.010

[20]   Allahverdi, A., Gupta, J.N. and Aldowaisan, T. (1999) A Review of Scheduling Research Involving Setup Considerations. Omega, 27, 219-239. http://dx.doi.org/10.1016/S0305-0483(98)00042-5

[21]   Allahverdi, A., Ng, C.T., Cheng, T.E. and Kovalyov, M.Y. (2008) A Survey of Scheduling Problems with Setup Times or Costs. European Journal of Operational Research, 187, 985-1032.
http://dx.doi.org/10.1016/j.ejor.2006.06.060

[22]   Vallada, E., Ruiz, R. and Minella, G. (2008) Minimising Total Tardiness in the m-Machine Flowshop Problem: A Review and Evaluation of Heuristics and Metaheuristics. Computers & Operations Research, 35, 1350-1373. http://dx.doi.org/10.1016/j.cor.2006.08.016