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Hybrid metaheuristics for scheduling of machines and transport robots in job shop environment

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Abstract

In real manufacturing environments, the control of some elements in systems based on robotic cells, such as transport robots has some difficulties when planning operations dynamically. The Job Shop scheduling Problem with Transportation times and Many Robots (JSPT-MR) is a generalization of the classical Job Shop scheduling Problem (JSP) where a set of jobs additionally have to be transported between machines by several transport robots. Hence, the JSPT-MR is more computationally difficult than the JSP presenting two NP-hard problems simultaneously: the job shop scheduling problem and the robot routing problem. This paper proposes a hybrid metaheuristic approach based on clustered holonic multiagent model for the JSPT-MR. Firstly, a scheduler agent applies a Neighborhood-based Genetic Algorithm (NGA) for a global exploration of the search space. Secondly, a set of cluster agents uses a tabu search technique to guide the research in promising regions. Computational results are presented using two sets of benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

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References

  1. Abdelmaguid TF, Nassef AO, Kamal BA, Hassan MF (2004) A hybrid ga/heuristic approach to the simultaneous scheduling of machines and automated guided vehicles. Int J Prod Res 42(2):267–281

    Article  MATH  Google Scholar 

  2. Anwar MF, Nagi R (1998) Integrated scheduling of material handling and manufacturing activities for just-in-time production of complex assemblies. Int J Prod Res 36(3):653–681

    Article  MATH  Google Scholar 

  3. Babu AG, Jerald J, Haq AN, Luxmi VM, Vigneswaralu TP (2010) Scheduling of machines and automated guided vehicles in fms using differential evolution. Int J Prod Res 48(16):4683–4699

    Article  MATH  Google Scholar 

  4. Bellifemine F, Poggi A, Rimassa G (1999) Jade - a fipa-compliant agent framework. In: Proceedings of the fourth International Conference and Exhibition on The Practical Application of Intelligent Agents and Multi-Agent Technology, pp 97–108

  5. Bilge U, Ulusoy G (1995) A time window approach to simultaneous scheduling of machines and material handling system in an fms. Oper Res 43(6):1058–1070

    Article  MATH  Google Scholar 

  6. Botti V, Giret A (2008) ANEMONA: A Multi-agent Methodology for Holonic Manufacturing Systems. Springer Series in Advanced Manufacturing. Springer

  7. Bozejko W, Uchronski M, Wodecki M (2010) The new golf neighborhood for the flexible job shop problem. In: Proceedings of the International Conference on Computational Science, pp 289–296

  8. Braga RAM, Rossetti RJF, Reis LP, Oliveira EC (2008) Applying multi-agent systems to simulate dynamic control in flexible manufacturing scenarios. In: European meeting on cybernetics and systems research, Austrian society for cybernetic studies, vol 2, pp 488–493

  9. Calabrese M (2011) Hierarchical-granularity holonic modelling. Doctoral thesis. Universita degli Studi di Milano, Milano

    Google Scholar 

  10. Caumond A, Lacomme P, Moukrim A, Tchernev N (2009) An milp for scheduling problems in an fms with one vehicle. Eur J Oper Res 199(3):706–722

    Article  MATH  Google Scholar 

  11. Deroussi L, Norre S (2010) Simultaneous scheduling of machines and vehicles for the flexible job shop problem. In: International Conference on Metaheuristics and Nature Inspired Computing, pp 1–2

  12. Deroussi L, Gourgand M, Tchernev N (2008) A simple metaheuristic approach to the simultaneous scheduling of machines and automated guided vehicles. Int J Prod Res 46(8):2143–2164

    Article  MATH  Google Scholar 

  13. Erol R, Sahin C, Baykasoglu A, Kaplanoglu V (2012) A multi-agent based approach to dynamic scheduling of machines and automated guided vehicles in manufacturing systems. Appl Soft Comput 12(6):1720–1732

    Article  Google Scholar 

  14. Ferber J (1999) Multi-agent Systems: An Introduction to Distributed Artificial Intelligence, 1st edn. Addison-Wesley Longman Publishing Co., Inc., Boston

    Google Scholar 

  15. Giret A, Botti V (2004) Holons and agents. J Intell Manuf 15(5):645–659

    Article  Google Scholar 

  16. Glover F, Kelly JP, Laguna M (1995) Genetic algorithms and tabu search: Hybrids for optimization. Comput Oper Res 22(1):111–134

    Article  MATH  Google Scholar 

  17. Hurink J, Knust S (2002) A tabu search algorithm for scheduling a single robot in a job-shop environment. Discret Appl Math 119(1-2):181–203

    Article  MathSciNet  MATH  Google Scholar 

  18. Hurink J, Knust S (2005) Tabu search algorithms for job-shop problems with a single transport robot. Eur J Oper Res 162(1):99–111

    Article  MATH  Google Scholar 

  19. Johnson SC (1967) Hierarchical clustering schemes. Psychometrika 32(3):241–254

    Article  Google Scholar 

  20. Jones A, Rabelo LC (1998) Survey of job shop scheduling techniques. Tech. rep., National Institute of Standards and Technology, Gaithersburg, USA

  21. Koestler A (1967) The Ghost in the Machine, 1st edn. Hutchinson, London

    Google Scholar 

  22. Komma VR, Jain PK, Mehta NK (2011) An approach for agent modeling in manufacturing on jade reactive architecture. Int J Adv Manuf Technol 52(9-12):1079–1090

    Article  Google Scholar 

  23. Lacomme P, Larabi M, Tchernev N (2007) A disjunctive graph for the job-shop with several robots. In: Multidisciplinary international conference on scheduling : Theory and applications. MISTA, Paris, pp 285–292

    Google Scholar 

  24. Lacomme P, Larabi M, Tchernev N (2013) Job-shop based framework for simultaneous scheduling of machines and automated guided vehicles. Int J Prod Econ 143(1):24–34

    Article  Google Scholar 

  25. Lee K, Yamakawa T, Lee KM (1998) A genetic algorithm for general machine scheduling problems. In: Proceedings of the second IEEE international Conference on Knowledge-Based Intelligent Electronic Systems, pp 60–66

  26. Lenstra JK, Kan A HGR (1979) Computational complexity of scheduling under precedence constraints. Annals of Discrete Mathematics 4:121–140

    Article  MathSciNet  MATH  Google Scholar 

  27. Lenstra JK, Kan A HGR (1981) Complexity of vehicle routing and scheduling problems. Networks 11 (2):221–227

    Article  Google Scholar 

  28. Mastrolilli M, Gambardella L (2000) Effective neighbourhood functions for the flexible job shop problem. J Sched 3(1):3–20

    Article  MathSciNet  MATH  Google Scholar 

  29. Muth JF, Thompson GL (1963) Industrial scheduling. International series in management. Prentice-Hall

  30. Pundit R, Palekar U (1990) Job shop scheduling with explicit material handling considerations. Tech. rep., Univ. of Illinois at Urbana-Champaign, Dept. of M. and I.E

  31. Raman N, Talbot FB, Rachamadgu RV (1986) Simultaneous scheduling of machines and material handling devices in automated manufacturing. In: Inproceedings of the 2nd ORSA/TIMS Conference on Flexible Manufacturing Systems, pp 455–466

  32. Reddy BSP, Rao CSP (2006) A hybrid multi-objective ga for simultaneous scheduling of machines and agvs in fms. Int J Adv Manuf Technol 31(5–6):602–613

    Article  Google Scholar 

  33. Sonmez AI, Baykasoglu A (1998) A new dynamic programming formulation of (nm) flow shop sequencing problems with due dates. Int J Prod Res 36(8):2269–2283

    Article  MATH  Google Scholar 

  34. Storn R, Price K (1995) Differential evolution: A simple and efficient adaptive scheme for global optimization over continuous spaces. Tech rep. International Computer Science Institute, Berkeley

    Google Scholar 

  35. Ulusoy G, Erifolu FS, Bilge U (1997) A genetic algorithm approach to the simultaneous scheduling of machines and automated guided vehicles. Comput Oper Res 24(3):335–351

    Article  MathSciNet  MATH  Google Scholar 

  36. Zhang Q, Manier H, Manier MA (2012) A genetic algorithm with tabu search procedure for flexible job shop scheduling with transportation constraints and bounded processing times. Comput Oper Res 39(7):1713–1723

    Article  MathSciNet  MATH  Google Scholar 

  37. Zhang Q, Manier H, Manier MA (2014) A modified shifting bottleneck heuristic and disjunctive graph for job shop scheduling problems with transportation constraints. Int J Prod Res 52(4):985–1002

    Article  Google Scholar 

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Authors and Affiliations

  1. Institut Supérieur de Gestion de Tunis, Université de Tunis, 41, Avenue de la Liberté, Cité Bouchoucha, Bardo, Tunis, Tunisie

    Houssem Eddine Nouri & Khaled Ghédira

  2. École Supérieure de Commerce de Tunis, Université de la Manouba, Tunis, Tunisie

    Olfa Belkahla Driss

Authors
  1. Houssem Eddine Nouri
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  2. Olfa Belkahla Driss
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  3. Khaled Ghédira
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Correspondence to Houssem Eddine Nouri.

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This paper does not contain any studies with human participants or animals performed by any of the authors.

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Nouri, H.E., Driss, O.B. & Ghédira, K. Hybrid metaheuristics for scheduling of machines and transport robots in job shop environment. Appl Intell 45, 808–828 (2016). https://doi.org/10.1007/s10489-016-0786-y

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  • DOI: https://doi.org/10.1007/s10489-016-0786-y

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