Skip to main content
SpringerLink
Log in

A Literature Survey on Metaheuristics in Production Systems

  • Chapter
Metaheuristics for Production Systems

Part of the book series: Operations Research/Computer Science Interfaces Series ((ORCS,volume 60))

Abstract

Typical problems in production systems are suboptimal production scheduling, long manufacturing lead times, inefficient inventory control, low work center utilization, etc. The solutions of these problems may need complex techniques while the classical techniques are insufficient to solve them. In this chapter we first classified the problems which may be faced in production systems and then the solution techniques called metaheuristics. Based on the keywords production problems and metaheuristics, our search was resulted in about 6,500 papers. The results have been summarized by tabular forms and graphical figures. The journals frequently publishing these papers have been also classified.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Anand S, McCord S, Sharma R, Balachander T (1999) An integrated machine vision based system for solving the nonconvex cutting stock problem using genetic algorithms. J Manuf Syst 18(6):396–415

    Article  Google Scholar 

  2. Bilgen B, Ozkarahan I (2004) Strategic and operational production and distribution models: a review. Int J Technol Manag (Special issue on Supply Chain Management: Integration Strategies based on New Technologies) 28(2):151–171

    Google Scholar 

  3. Blum C (2008) Beam-ACO for simple assembly line balancing. Inf J Comput 20(4):618–627

    Article  Google Scholar 

  4. Boudia M, Prins C (2009) A memetic algorithm with dynamic population management for an integrated production-distribution problem. Eur J Oper Res 195(3):703–715

    Article  Google Scholar 

  5. Cardona-Valdes Y, Alvarez A, Pacheco J (2014) Metaheuristic procedure for a bi-objective supply chain design problem with uncertainty. Transp Res Part B-Methodol 60:66–84

    Article  Google Scholar 

  6. Carle M-A, Martel A, Zufferey N (2012) The CAT metaheuristic for the solution of multi-period activity-based supply chain network design problems. Int J Prod Econ 139(2):664–677

    Article  Google Scholar 

  7. Caserta M, Quinonez RE (2009) A cross entropy-Lagrangean hybrid algorithm for the multi-item capacitated lot-sizing problem with setup times. Comput Oper Res 36(2):530–548

    Article  Google Scholar 

  8. Caserta M, Stefan V (2013) A math-heuristic Dantzig-Wolfe algorithm for capacitated lot sizing. In: 6th conference on learning and intelligent optimization (Lion), Paris, Jan 2012. Ann Math Artif Intell 69(2 Special Issue: SI):207–224

    Google Scholar 

  9. Cavin L, Fischer U, Glover F, Hungerbuhler K (2004) Multi-objective process design in multi-purpose batch plants using a Tabu Search optimization algorithm. Comput Chem Eng 28(4):459–478

    Article  Google Scholar 

  10. Chiang W-C, Russell R, Xu X et al (2009) A simulation/metaheuristic approach to newspaper production and distribution supply chain problems. Int J Prod Econ 121(2):752–767

    Article  Google Scholar 

  11. Coelho LC, Cordeau J-F, Laporte G (2014) Thirty years of inventory routing. Transp Sci 48(1):1–19

    Article  Google Scholar 

  12. Copado-Mendez PJ, Blum C, Guillen-Gosalbez G (2013) Large neighbourhood search applied to the efficient solution of spatially explicit strategic supply chain management problems. Comput Chem Eng 49:114–126

    Article  Google Scholar 

  13. Darwis SM (2012) Soft computing applied to the build of textile defects inspection system. IET Comput Vis 7(5):373–381

    Article  Google Scholar 

  14. Duan Q, Liao TW (2013) A new age-based replenishment policy for supply chain inventory optimization of highly perishable products. Int J Prod Econ 145(2):658–671

    Article  Google Scholar 

  15. Fattahi P, Salehi M (2009) Sequencing the mixed-model assembly line to minimize the total utility and idle costs with variable launching interval. Int J Adv Manuf Technol 45(9–10):987–998

    Article  Google Scholar 

  16. Gagne C, Gravel M, Price WL (2006) Solving real car sequencing problems with ant colony optimization. Eur J Oper Res 174(3):1427–1448

    Article  Google Scholar 

  17. Garey MR, Johnson DS, Sethi R (1976) The complexity of flowshop and jobshop scheduling. Math Oper Res 1(2):117–129

    Article  Google Scholar 

  18. Geetha S, Vanathi PT, Poonthalir G (2012) Metaheuristic approach for the multi-depot vehicle routing problem. Appl Artif Intell 26(9):878–901

    Article  Google Scholar 

  19. Geraili A, Sharma P, Romagnoli JA (2014) A modeling framework for design of nonlinear renewable energy systems through integrated simulation modeling and metaheuristic optimization: applications to biorefineries. Comput Chem Eng 61:102–117

    Article  Google Scholar 

  20. Golfeto RR, Moretti AC, Neto LLS (2008) A grasp metaheuristic for the ordered cutting stock problem. Ingeniare. Revista chilena de ingeniería, 16(3):421–427

    Google Scholar 

  21. Graham R (1966) Bounds for certain multiprocessing anomalies. Bell Syst Tech J 45:1563–1581. doi:10.1002/j.1538-7305.1966.tb01709

    Article  Google Scholar 

  22. Han Y, Kaku I, Tang J (2011) A scatter search approach for uncapacitated multilevel lot-sizing problems. Int J Innov Comput Inf Control 7(8):4833–4847

    Google Scholar 

  23. Homberger J (2008) A parallel genetic algorithm for the multilevel unconstrained lot-sizing problem. Inf J Comput 20(1):124–132

    Article  Google Scholar 

  24. Jabbarizadeh F, Zandieh M, Talebi D (2009) Hybrid flexible flowshops with sequence-dependent setup times and machine availability constraints. Comput Ind Eng 57(3):949–957

    Article  Google Scholar 

  25. Jarboui B, Siarry P, Teghem J (ed) (2013) Metaheuristics for production scheduling. Wiley, Hoboken. ISBN: 978-1-84821-497-2

    Google Scholar 

  26. Jarboui B, Siarry P, Teghem J (2013) Metaheuristics for production scheduling. Wiley Online Library, Hoboken

    Book  Google Scholar 

  27. Johnson SM (1954) Optimal two and three stage production schedules with setup times included. Nav Res Logist Q 1(1):61–68

    Article  Google Scholar 

  28. Kosucuoglu D, Bilge U (2012) Material handling considerations in the FMS loading problem with full routing flexibility. Int J Prod Res 50(22):6530–6552

    Article  Google Scholar 

  29. Krishna AG, Rao KM (2006) Optimisation of operations sequence in CAPP using an ant colony algorithm. Int J Adv Manuf Technol 29(1–2):159–164

    Article  Google Scholar 

  30. Li X, Baki MF, Aneja YP (2010) An ant colony optimization metaheuristic for machine-part cell formation problems. Comput Oper Res 37(12):2071–2081

    Article  Google Scholar 

  31. Lian K, Zhang C, Shao X, Liang G (2012) Optimization of process planning with various flexibilities using an imperialist competitive algorithm. Int J Adv Manuf Technol 59(5–8):815–828

    Article  Google Scholar 

  32. Lin S-W, Ying K-C (2013) Increasing the total net revenue for single machine order acceptance and scheduling problems using an artificial bee colony algorithm. J Oper Res Soc 64(2):293–311

    Article  Google Scholar 

  33. Liu C-H (2011) Using genetic algorithms for the coordinated scheduling problem of a batching machine and two-stage transportation. Appl Math Comput 217(24):10095–10104

    Article  Google Scholar 

  34. Luo H, Huang G, Yuan S (2012) Hybrid flowshop scheduling with family setup time and inconsistent family formation. Int J Prod Res 50(6):1457–1475

    Article  Google Scholar 

  35. Malakooti B (2013) Operations and production systems with multiple objectives. John Wiley, New York. ISBN 978-1-118-58537-5

    Google Scholar 

  36. Mitra K (2008) Genetic algorithms in polymeric material production, design, processing and other applications: a review. Int Mater Rev 53(5):275–297

    Article  Google Scholar 

  37. Musa R, Arnaout JP, Chen FF (2012) Optimization-simulation-optimization based approach for proactive variation reduction in assembly. Robot Comput-Integrate Manuf 28:613–620

    Article  Google Scholar 

  38. Onwubolu GC, Mutingi M (2001) A genetic algorithm approach to cellular manufacturing systems. Comput Ind Eng 39(1–2):125–144

    Article  Google Scholar 

  39. Onwubolu GC, Songore V (2000) A tabu search approach to cellular manufacturing systems. Prod Plan Control 11(2):153–164

    Article  Google Scholar 

  40. Osman IH, Laporte G (1996) Metaheuristics: a bibliography. Ann Oper Res 63:513–623

    Article  Google Scholar 

  41. Ozbakır L, Baykasoglu A, Kulluk S (2011) Rule extraction from artificial neural networks to discover causes of quality defects in fabric production. Neural Comput Appl 20:1117–1128

    Article  Google Scholar 

  42. Ruiz-Rodriguez FJ, Gomez-Gonzalez M, Jurado F (2013) Optimization of radial systems with biomass fueled gas engine from a metaheuristic and probabilistic point of view. Energy Convers Manag 65(Special Issue: SI):343–350

    Google Scholar 

  43. Russell R (2013) A constraint programming approach to designing a newspaper distribution system. Int J Prod Econ 145(1):132–138

    Article  Google Scholar 

  44. Sabuncuoglu I, Erel E, Alp A (2009) Ant colony optimization for the single model U-type assembly line balancing problem. Int J Prod Econ 120(2 Special Issue: SI):287–300

    Google Scholar 

  45. Shen Q, Chen H, Chu F (2011) Multi-mode transportation planning of crude oil via Greedy randomized adaptive search and path relinking. Trans Inst Meas Control 33(3–4):456–475

    Article  Google Scholar 

  46. Souier M, Sari Z, Hassam A (2013) Real-time rescheduling metaheuristic algorithms applied to FMS with routing flexibility. Int J Adv Manuf Technol 64(1–4):145–164

    Article  Google Scholar 

  47. Tarantilis CD, Kiranoudis CT (2002) A list-based threshold accepting method for job shop scheduling problems. Int J Prod Econ 77(2):159–171. Article Number: PII S0925-5273(01)00231-6

    Google Scholar 

  48. Uncu O, Elghoneimy E, Gruver WA (2005) Jag sequencing in rough mill operations. In: Proceedings of the IEEE international conference on systems, man and cybernetics, Waikoloa, 10–12 Oct 2005. Book Series: IEEE international conference on systems man and cybernetics conference proceedings, vol 1–4, pp 300–305

    Google Scholar 

  49. Van Volsem S, Dullaert W, Van Landeghem H (2007) An evolutionary algorithm and discrete event simulation for optimizing inspection strategies for multi-stage processes. Eur J Oper Res 179(3):621–633

    Article  Google Scholar 

  50. Vasant P (2010) Hybrid simulated annealing and genetic algorithms for industrial production management problems. Int J Comput Methods 7(2):279–297

    Article  Google Scholar 

  51. Xhafa F, Abraham A (eds) (2008) Metaheuristics for scheduling in industrial and manufacturing applications. Studies in computational intelligence, vol 128. Springer, Berlin. ISBN 978-3-540-78985-7

    Google Scholar 

  52. Yalaoui N, Ouazene Y, Yalaoui F (2013) Fuzzy-metaheuristic methods to solve a hybrid flow shop scheduling problem with pre-assignment. Int J Prod Res 51(12):3609–3624

    Article  Google Scholar 

  53. Zhang R, Song S, Wu C (2013) A simulation-based differential evolution algorithm for stochastic parallel machine scheduling with operational considerations. Int Trans Oper Res 20(4):533–557

    Article  Google Scholar 

  54. Zobolas GI, Tarantilis CD, Ioannou G (2009) A hybrid evolutionary algorithm for the job shop scheduling problem. J Oper Res Soc 60(2):221–235

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Industrial Engineering Department, Istanbul Technical University, 34367, Macka Istanbul, Turkey

    Sezi Çevik Onar, Başar Öztayşi, Cengiz Kahraman & Seda Yanık

  2. Laboratoire d’optimisation des systèmes industriels (LOSI), Institut Charles Delaunay (ICD), UMR CNRS 6281, Université de Technologie de Troyes, 12 rue Marie Curie, CS 42060, 10004, Troyes Cedex, Troyes, France

    Özlem Şenvar

Authors
  1. Sezi Çevik Onar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Başar Öztayşi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cengiz Kahraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Seda Yanık
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Özlem Şenvar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cengiz Kahraman .

Editor information

Editors and Affiliations

  1. CRISTAL Laboratory, Lille 1 University, Villeneuve d'Ascq, France

    El-Ghazali Talbi

  2. LOSI Laboratory, University of Technology of Troyes, Troyes, France

    Farouk Yalaoui

  3. LOSI Laboratory, University of Technology of Troyes, Troyes, France

    Lionel Amodeo

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Onar, S., Öztayşi, B., Kahraman, C., Yanık, S., Şenvar, Ö. (2016). A Literature Survey on Metaheuristics in Production Systems. In: Talbi, EG., Yalaoui, F., Amodeo, L. (eds) Metaheuristics for Production Systems. Operations Research/Computer Science Interfaces Series, vol 60. Springer, Cham. https://doi.org/10.1007/978-3-319-23350-5_1

Download citation

Publish with us

Policies and ethics

Search

Navigation