Share This Article:

Mathematical Models to Simultaneously Determine Overtime Requirements and Schedule Cells

Abstract Full-Text HTML XML Download Download as PDF (Size:1059KB) PP. 58-72
DOI: 10.4236/eng.2015.72006    2,202 Downloads   2,783 Views   Citations

ABSTRACT

The problem studied in this paper was inspired from an actual textile company. The problem is more complex than usual scheduling problems in that we compute overtime requirements and make scheduling decisions simultaneously. Since having tardy jobs is not desirable, we allow overtime to minimize the number of tardy jobs. The overall objective is to maximize profits. We present various mathematical models to solve this problem. Each mathematical model reflects different overtime workforce hiring practices. An experimentation has been carried out using eight different data sets from the samples of real data collected in the above mentioned textile company. Mathematical Model 2 was the best mathematical model with respect to both profit and execution time. This model considered partial overtime periods and also allowed different overtime periods on cells. We could solve problems up to 90 jobs per period. This was much more than what the mentioned textile company had to handle on a weekly basis. As a result, these models can be used to make these decisions in many industrial settings.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Süer, G. and Mathur, K. (2015) Mathematical Models to Simultaneously Determine Overtime Requirements and Schedule Cells. Engineering, 7, 58-72. doi: 10.4236/eng.2015.72006.

References

[1] Suresh, N.C. and Kay, J.M. (1998) Group Technology and Cellular Manufacturing: A State-of-the-Art Synthesis of Research and Practice. Kluwer Academic, Boston.
http://dx.doi.org/10.1007/978-1-4615-5467-7
[2] Süer, G.A., Saiz, M., Dagli, C. and Gonzalez, W. (1995) Manufacturing Cell Loading Rules and Algorithms for Connected Cells. Manufacturing Research and Technology Journal, 24, 97-127.
http://dx.doi.org/10.1016/S1572-4417(06)80038-0
[3] Süer, G.A., Saiz, M. and Gonzalez, W. (1999) Evaluation of Manufacturing Cell Loading Rules for Independent Cells. International Journal of Production Research, 37, 3445-3468.
http://dx.doi.org/10.1080/002075499190130
[4] Süer, G.A., Vazquez, R. and Cortes, M. (2005) A Hybrid Approach of Genetic Algorithms and Local Optimizers in Cell Loading. Computers and Industrial Engineering, 48, 625-641.
http://dx.doi.org/10.1016/j.cie.2003.03.005
[5] Süer, G.A., Arikan, F. and Babayigit, C. (2008) Bi-Objective Cell Loading Problem with Non-Zero Setup Times with Fuzzy Aspiration Levels in Labour Intensive Manufacturing Cells. International Journal of Production Research, 46, 371-404.
http://dx.doi.org/10.1080/00207540601138460
[6] Süer, G.A., Arikan, F. and Babayigit, C. (2009) Effects of Different Fuzzy Operators on Fuzzy Bi-Objective Cell Loading Problem in Labor-Intensive Manufacturing Cells. Computers & Industrial Engineering, 56, 476-488.
http://dx.doi.org/10.1016/j.cie.2008.02.001
[7] Süer, G.A. and Dagli, C. (2005) Intra-Cell Manpower Transfers and Cell Loading in Labor-Intensive Manufacturing Cells. Computers & Industrial Engineering, 48, 643-655.
http://dx.doi.org/10.1016/j.cie.2003.03.006
[8] Süer, G.A., Cosner, J. and Patten, A. (2009) Models for Cell Loading and Product Sequencing in Labor-Intensive Cells. Computers & Industrial Engineering, 56, 97-105.
http://dx.doi.org/10.1016/j.cie.2008.04.002
[9] Yarimoglu, F. (2009) Cell Loading and Product Sequencing Subject to Manpower Restrictions in Synchronized Manufacturing Cells, Ohio University.
http://etd.ohiolink.edu/send-pdf.cgi/Yarimoglu%20Fatih.pdf?ohiou1234899632
[10] Nakamura, N., Yoshida, T. and Hitomi, K. (1978) Group Production Scheduling for Minimum Total Tardiness Part(I), AIIE Transactions, 10, 157-162.
[11] Hitomi, K. and Ham, I. (1976) Operations Scheduling for Group Technology Applications. CIRP Annals, 25, 419-422.
[12] Ham, I., Hitomi, K., Nakamura, N. and Yoshida, T. (1979) Optimal Group Scheduling and Machining-Speed Decision under Due-Date Constraints. Transactions of the ASME Journal of Engineering for Industry, 101, 128-134.
[13] Pan, J.C.H. and Wu, C.C. (1998) Single Machine Group Scheduling to Minimize Mean Flow Time Subject to Due Date Constraints. Production Planning and Control, 9, 366-370.
http://dx.doi.org/10.1080/095372898234091
[14] Gupta, J.N.D. and Chantaravarapan, S. (2008) Single Machine Group Scheduling with Family Setups to Minimize Total Tardiness. International Journal of Production Research, 46, 1707-1722.
http://dx.doi.org/10.1080/00207540601009976
[15] Süer, G.A. and Mese, E.M. (2011) Cell Loading and Family Scheduling for Jobs with Individual Due Dates. In: Modrák, V. and Pandian, R.S., Eds., Operations Management Research and Cellular Manufacturing Systems: Innovative Methods and Approaches, IGI Global, Hershey, 208-226.
[16] Süer, G.A., Santos, J. and Vazquez, R. (1999) Scheduling Rotary Injection Molding Machines. Proceedings of the Second Asia-Pacific Conference on Industrial Engineering and Management Systems, Kanazawa, 30-31 October 1999, 319-322.
[17] Süer, G.A., Subramanian, A. and Huang, J. (2009) Heuristic Procedures and Mathematical Models for Cell Loading and Scheduling in a Shoe Manufacturing Company. Computers & Industrial Engineering, 56, 462-475.
http://dx.doi.org/10.1016/j.cie.2008.10.008
[18] Huang, J., Süer, G.A. and Urs, S.B.R. (2011) Genetic Algorithm for Rotary Machine Scheduling with Dependent Processing Times. Journal of Intelligent Manufacturing, 23, 1931-1948.
http://dx.doi.org/10.1007/s10845-011-0521-9
[19] Mathur, K. and Süer, G.A. (2013) Math Modeling and GA Approach to Simultaneously Make Overtime Decisions, Load Cells and Sequence Products. Computers & Industrial Engineering, 66, 614-624.
http://dx.doi.org/10.1016/j.cie.2013.08.012
[20] Maxwell, W.L. (1970) On Sequencing n Jobs on One Machine to Minimize the Number of Late Jobs. Management Science, 16, 295-297.
http://dx.doi.org/10.1287/mnsc.16.5.295
[21] Süer, G.A., Pico, F. and Santiago, A. (1997) Identical Machine Scheduling to Minimize the Number of Tardy Jobs When Lot-Splitting Is Allowed. Computers & Industrial Engineering, 33, 277-280.
http://dx.doi.org/10.1016/S0360-8352(97)00092-2

  
comments powered by Disqus

Copyright © 2019 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.