Abstract
This paper focuses on a computational tool for scheduling and sequencing sugarcane vehicles for dump tippler machines at the mill yard of a sugar mill, which can be represented as an NP-hard problem for parallel capacitated machines with machine restrictions, job grouping, and sequencing independent setup time. This research aims to determine the optimal sequencing of jobs, i.e. minimizing the makespan by considering machine restrictions, capacitated machines, group size, number of jobs, and the constraints of the sugar mill. In the considered problem machines alternatively operate, that distinguishes it from a general parallel machine problem. The mixed integer linear programing model is developed for solving the small-scale problem instances. Large-scale instances are handled by four heuristics, and four differential evolution (DE) metaheuristics. In order to improve the computational results, solution quality and computation time were considered. In addition, modified DE algorithms were used in encoding operation (initial solution), mutation and local search operation. The computational results revealed that the modified DE algorithms had higher relative improvement on the makespan. Furthermore, this decision-making support tool was implemented as a prototype in the sector of cane and sugar industry in Thailand and extended to other similar industries.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arjona E, Bueno G, Salazar L (2001) An activity simulation model for the analysis of the harvesting and transportation systems of a sugarcane plantation. Comput Elect Agric 32(3):247–264
Astika IW, Cahyoutomo R, Lilik Mulyantara FX (2001) Development computer software for optimum scheduling of farm machinery operations in a sugarcane plantation. IFAC Proc Vol 34(11):217–220. https://doi.org/10.1016/S1474-6670(17)34135-6
Baikow VE (2013) Manufacture and refining of raw cane sugar. Manuf Refin Raw Cane Sugar. https://doi.org/10.1016/b978-1-4832-3212-6.50016-5
Bocanegra-Herrera CC, Vidal-Holguín CJ (2016) Development of a simulation model as a decision support system for sugarcane supply. DYNA 83(198):180
Chakravarthy SR, Karatza HD (2013) Two-server parallel system with pure space sharing and Markovian arrivals. Comput Operat Res 40(1):510–519
Chiang C-W, Lee W-P, Heh J-S (2010) A 2-Opt based differential evolution for global optimization. Applied Soft Computing 10(4):1200–1207
Centeno G, Armacost RL (1997) Parallel machine scheduling with release time and machine eligibility restrictions. Comput Ind Eng 33(1–2):273–276. https://doi.org/10.1016/S0360-8352(97)00091-0
Dechampai D et al (2017) A differential evolution algorithm for the capacitated VRP with flexibility of mixing pickup and delivery services and the maximum duration of a route in poultry industry. J Intell Manuf 28(6):1357–1376. https://doi.org/10.1007/s10845-015-1055-3
Dolgui A et al (2009) Multi-product lot-sizing and scheduling on unrelated parallel machines to minimize makespan. In: IFAC proceedings volumes (IFAC-PapersOnline). IFAC. https://doi.org/10.3182/20090603-3-ru-2001.0553
Fox K, Korupolu M (2013) Weighted flowtime on capacitated machines. In:Proceedings of the 2013 annual ACM-SIAM symposium on discrete algorithms, pp 129--143. Retrieved from https://dblp.uni-trier.de/db/conf/soda/soda2013.html#FoxK13. https://doi.org/10.1137/1.9781611973105.10
Garey MR, Johnson DS (1978) “Strong” NP-completeness results: motivation, examples, and implications. J ACM 25(3):499–508. https://doi.org/10.1145/322077.322090
Gokhale R, Mathirajan M (2012) Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing. Int J Adv Manuf Technol 60(9–12):1099–1110. https://doi.org/10.1007/s00170-011-3653-3
Higgins A et al (1998) Optimising harvest date in sugar production: a case study for the Mossman mill region in Australia: I. Development of operations research model and solution. Field Crops Res 57(2):153–162. https://doi.org/10.1016/S0378-4290(97)00116-0
Higgins A, Davies I (2005) A simulation model for capacity planning in sugarcane transport. Comput Electron Agric 47(2):85–102
Hu X, Bao JS, Jin Y (2010) Minimising makespan on parallel machines with precedence constraints and machine eligibility restrictions. Int J Prod Res 48(6):1639–1651. https://doi.org/10.1080/00207540802620779
Iannoni AP, Morabito R (2006) A discrete simulation analysis of a logistics supply system. Transport Res Part E: Logist and Transport Rev 42(3):191–210
Jenkins GH (2013) Introduction to cane sugar technology. Elsevier, Amsterdam
Kachitvichyanukul V (2012) Comparison of three evolutionary algorithms: GA, PSO, and DE. Ind Eng Manag Syst 11(3):215–223. https://doi.org/10.7232/iems.2012.11.3.215
Lee K, Leung JYT, Pinedo ML (2011) Scheduling jobs with equal processing times subject to machine eligibility constraints. J Sched 14(1):27–38. https://doi.org/10.1007/s10951-010-0190-0
Leung JY, Li C (2008) Scheduling with processing set restrictions: a survey. Int J Prod Econ 116(2):251–262
Li YL, Zhang J (2011) A new differential evolution algorithm with dynamic population partition and local restart. In: Proceedings of the 13th annual conference on genetic and evolutionary computation, pp 1085–1092. https://doi.org/10.1145/2001576.2001723
Martinez S, Dauzère-Pérès S, Guéret C, Mati Y, Sauer N (2006) Complexity of flowshop scheduling problems with a new blocking constraint. Euro J Operat Res 169(3):855–864
Masoud M, Kozan E, Kent G (2015) Hybrid metaheuristic techniques for optimising sugarcane rail operations. Int J Prod Res 53(9):2569–2589. https://doi.org/10.1080/00207543.2014.957870
Moonsri K, Sethanan K, Sangsawang C (2015) Metaheuristics for scheduling unrelated parallel machines with sequence-dependent setup time and machine eligibility. Chiang Mai Univ J Nat Sci 14(4):431–446. https://doi.org/10.12982/cmujns.2015.0097
Muchow R et al (1998) Optimising harvest date in sugar production: a case study for the Mossman mill region in Australia. Field Crops Res 57(3):243–251. https://doi.org/10.1016/S0378-4290(97)00135-4
Nait Tahar D, Yalaoui F, Chu C, Amodeo L (2006) A linear programming approach for identical parallel machine scheduling with job splitting and sequence-dependent setup times. Int J Prod Eco 99(1–2):63–73
Nearchou AC (2006) Meta-heuristics from nature for the loop layout design problem. Int J Product Eco 101(2):312–328
Office of Global Analysis (2015) Sugar: world markets and trade global sugar consumption outpaces production, foreign agricultural service. http://usda.mannlib.cornell.edu/usda/fas/sugar//2010s/2015/sugar-11-19-2015.pdf. Accessed 2 Sept 2016
Office of the Cane and Sugar Board (2017) The annual report of sugarcane plantation and sugar production in 2016/2017. http://www.ocsb.go.th/upload/journal/fileupload/923-9999.pdf. Accessed 2 Sept 2016
Pinedo ML (1995) Scheduling: Theory, algorithms, and systems. Theory, Algorithms, and Systems, Scheduling. https://doi.org/10.1007/978-0-387-78935-4
Pitakaso R, Sethanan K (2016) Modified differential evolution algorithm for simple assembly line balancing with a limit on the number of machine types. Eng Optim 48(2):253–271. https://doi.org/10.1080/0305215X.2015.1005082
Potts CN, Kovalyov MY (2000) Scheduling with batching: a review. Eur J Oper Res 120(2):228–249. https://doi.org/10.1016/S0377-2217(99)00153-8
Rabadi G, Moraga R, Al-Salem A (2006) Heuristics for the unrelated parallel machine scheduling problem with setup times. J Intell Manuf 17:85–97. https://doi.org/10.1007/s10845-005-5514-0
Sartori MMP et al (2001) Determination of the optimal quantity of crop residues for energy in sugarcane crop management using linear programming in variety selection and planting strategy. Energy 26(11):1031–1040. https://doi.org/10.1016/S0360-5442(01)00052-4
Silva C, Magalhaes JM (2006) Heuristic lot size scheduling on unrelated parallel machines with applications in the textile industry. Comput Indus Eng 50(1–2):76–89
Sethanan K, Neungmatcha W (2014) Multi-objective particle swarm optimization for mechanical harvester route planning of sugarcane field operations. Eur J Oper Res 252(3):969–984. https://doi.org/10.1016/j.ejor.2016.01.043
Sethanan K, Pitakaso R (2016a) Differential evolution algorithms for scheduling raw milk transportation. Comput Electron Agric 121:245–259. https://doi.org/10.1016/j.compag.2015.12.021
Sethanan K, Pitakaso R (2016b) Improved differential evolution algorithms for solving generalized assignment problem. Expert Syst Appl 45:450–459. https://doi.org/10.1016/j.eswa.2015.10.009
Sharma R et al (2010) An agent based dynamic resource scheduling model with FCFS-job grouping strategy in grid computing. World Acad Sci Eng Technol 4(4):823–827
Storn R, Price K (1997) Differential evolution—a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11(4):341–359. https://doi.org/10.1023/A:1008202821328
Tinnongwatthana T (2013) Sugar cane harvest and transportation, Office of the Cane and Sugar Board. http://oldweb.ocsb.go.th/udon/Alltext/1.Article/01-ArticleP9.1.htm. Accessed 2 Sept 2016
USDA (2017) Record global production spurs record consumption sugar overview. https://public.govdelivery.com/accounts/USDAFAS/subscriber/new. Accessed 2 Sept 2016
Webster S, Baker K (1995) Scheduling groups of jobs on a single machine. Oper Res 43(4):692–703. https://doi.org/10.1287/opre.43.4.692
Wu X, Che A (2018) A memetic differential evolution algorithm for energy-efficient parallel machine scheduling. Omega (United Kingdom). https://doi.org/10.1016/j.omega.2018.01.001
Weaver VM, Johnson M, Kasichayanula K, Ralph J, Luszczek P, Terpstra D, Moore S (2012) Measuring energy and power with PAPI. In: 2012 41st international conference on parallel processing workshops, pp 262–268. IEEE. https://doi.org/10.1109/ICPPW.2012.39
Yuan S et al (2011) A job grouping approach for planning container transfers at automated seaport container terminals. Adv Eng Inform 25(3):413–426. https://doi.org/10.1016/j.aei.2011.01.004
Yalaoui F, Chu C (2003) An efficient heuristic approach for parallel machine scheduling with job splitting and sequence-dependent setup times. IIE Transactions 35(2):183–190
Yanyan Z, Tieke L, Bailin W (2011) Scheduling parallel multiple capacitated machines with sequence-dependent constraint. In: 2011 international conference on E-business and E-government, ICEE2011 - Proceedings, pp 2570–2573. https://doi.org/10.1109/ICEBEG.2011.5882009
Acknowledgments
This study was supported by the Thailand Research Fund (TRF) through the Research and Researchers for Industries-RRi (Grant No. PHD58I0041) in collaboration with Rajburi Sugar Company Limited, Department of Business Administration, Faculty of Business, Economics and Statistics, University of Vienna, Vienna, Austria, and Research Unit on System Modeling for Industry (SMI), Department of Industrial Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen, Thailand. Thanks are also due to the staff of the sugar mill for their assistance and facilities given during the time of this research. The authors would also like to thank Prof. Somnuk Theerakulpisut and Mr. Ian Thomas for English language review of the manuscript.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Kusoncum, C., Sethanan, K., Hartl, R.F. et al. Modified differential evolution and heuristic algorithms for dump tippler machine allocation in a typical sugar mill in Thailand. Oper Res Int J 22, 5863–5895 (2022). https://doi.org/10.1007/s12351-020-00597-z
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12351-020-00597-z