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Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

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Abstract

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

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References

  1. Halevi G, Weill R. Principles of Process Planning: A Logical Approach. Rotterdam: Springer, 1995

    Book  Google Scholar 

  2. Niebel B W. Mechanized process selection for planning new designs. In: ASME 33rd Annual Meeting collected papers, 1965, 65 (4): 737

    Google Scholar 

  3. Conway R W, Maxwell W L, Miller L W. Theory of scheduling. Cranbury: Addison-Wesley, 1967

    MATH  Google Scholar 

  4. Chryssolouris G, Chan S, Cobb W. Decision making on the factory floor: An integrated approach to process planning and scheduling. Robotics and Computer-integrated Manufacturing, 1984, 1(3–4): 315–319

    Article  Google Scholar 

  5. Mamalis A, Malagardis I, Kambouris K. On-line integration of a process planning module with production scheduling. International Journal of Advanced Manufacturing Technology, 1996, 12(5): 330–338

    Article  Google Scholar 

  6. Zhang J, Gao L, Chan F T, et al. A holonic architecture of the concurrent integrated process planning system. Journal of Materials Processing Technology, 2003, 139(1–3): 267–272

    Article  Google Scholar 

  7. Wang L, Hao Q, Shen W. A novel function block based integration approach to process planning and scheduling with execution control. International Journal of Manufacturing Technology and Management, 2007, 11(2): 228–250

    Article  Google Scholar 

  8. Chryssolouris G, Chan S, Suh N P. An integrated approach to process planning and scheduling. CIRP Annals, 1985, 34(1): 413–417

    Article  Google Scholar 

  9. Min L, Li B, Zhang S. Modeling integrated CAPP/PPS systems. Computers & Industrial Engineering, 2004, 46(2): 275–283

    Article  Google Scholar 

  10. Kumar M, Rajotia S. Integration of process planning and scheduling in a job shop environment. International Journal of Advanced Manufacturing Technology, 2006, 28(1–2): 109–116

    Article  Google Scholar 

  11. Yang Y N, Parsaei H R, Leep H R. A prototype of a feature-based multiple-alternative process planning system with scheduling verification. Computers & Industrial Engineering, 2001, 39(1–2): 109–124

    Article  Google Scholar 

  12. Grabowik C, Kalinowski K, Monica Z. Integration of the CAD/CAPP/PPC systems. Journal of Materials Processing Technology, 2005, 164–165: 1358–1368

    Article  Google Scholar 

  13. Morad N, Zalzala A. Genetic algorithms in integrated process planning and scheduling. Journal of Intelligent Manufacturing, 1999, 10(2): 169–179

    Article  Google Scholar 

  14. Palmer G J. A simulated annealing approach to integrated production scheduling. Journal of Intelligent Manufacturing, 1996, 7(3): 163–176

    Article  Google Scholar 

  15. Kim Y K, Park K, Ko J. A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling. Computers & Operations Research, 2003, 30(8): 1151–1171

    Article  MathSciNet  MATH  Google Scholar 

  16. Li W, Mc Mahon C A. A simulated annealing-based optimization approach for integrated process planning and scheduling. International Journal of Computer Integrated Manufacturing, 2007, 20(1): 80–95

    Article  Google Scholar 

  17. Li X, Gao L, Zhang G, et al. A genetic algorithm for integration of process planning and scheduling problem. In: Xiong C, Liu H, Huang Y, et al., eds. Intelligent Robotics and Applications. Berlin: Springer, 2008, 495–502

    Chapter  Google Scholar 

  18. Lv Q L, Lv S. An improved genetic algorithm for integrated process planning and scheduling. The International Journal of Advanced Manufacturing Technology, 2012, 58(5–8): 727–740

    Google Scholar 

  19. Li X, Gao L, Zhang C, et al. A review on integrated process planning and scheduling. International Journal of Manufacturing Research, 2010, 5(2): 161–180

    Article  Google Scholar 

  20. Phanden R K, Jain A, Verma R. Integration of process planning and scheduling: A state-of-the-art review. International Journal of Computer Integrated Manufacturing, 2011, 24(6): 517–534

    Article  Google Scholar 

  21. Tan W, Khoshnevis B. Integration of process planning and scheduling—Review. Journal of Intelligent Manufacturing, 2000, 11(1): 51–63

    Article  Google Scholar 

  22. Wang L, Shen W, Hao Q. An overview of distributed process planning and its integration with scheduling. International Journal of Computer Applications in Technology, 2006, 26(1/2): 3–14

    Article  Google Scholar 

  23. Baykasoglu A, Özbakir L. Analyzing the effect of dispatching rules on the scheduling performance through grammar based flexible scheduling system. International Journal of Production Economics, 2010, 124(2): 369–381

    Article  Google Scholar 

  24. Wang Y F, Zhang Y, Fuh J Y H. A PSO-based multi-objective optimization approach to the integration of process planning and scheduling, In: 2010 8th IEEE International Conference on Control and Automation (ICCA). Xiamen: IEEE, 2010, 614–619

    Google Scholar 

  25. Rajkumar M, Asokan P, Page T, et al. A GRASP algorithm for the integration of process planning and scheduling in a flexible jobshop. International Journal of Manufacturing Research, 2010, 5(2): 230–251

    Article  Google Scholar 

  26. Li X, Gao L, Li W. Application of game theory based hybrid algorithm for multi-objective integrated process planning and scheduling. Expert Systems with Applications, 2012, 39(1): 288–297

    Article  Google Scholar 

  27. Mohapatra P, Benyoucef L, Tiwari M. Integration of process planning and scheduling through adaptive setup planning: A multiobjective approach. International Journal of Production Research, 2013, 51(23–24): 7190–7208

    Article  Google Scholar 

  28. Zitzler E, Thiele L. Multiobjective evolutionary algorithms: A comparative case study and the strength Pareto approach. IEEE Transactions on Evolutionary Computation, 1999, 3(4): 257–271

    Article  Google Scholar 

  29. Deb K. Multi-Objective Optimization Using Evolutionary Algorithms. Chichester: John Wiley & Sons, 2012

    Google Scholar 

  30. Branke J, Deb K, Miettinen K, et al. Multiobjective Optimization: Interactive and Evolutionary Approaches. Berlin: Springer, 2008

    Book  Google Scholar 

  31. Kis T, Kiritsis D, Xirouchakis P, et al. A Petri net model for integrated process and job shop production planning. Journal of Intelligent Manufacturing, 2000, 11(2): 191–207

    Article  Google Scholar 

  32. Ho Y C, Moodie C L. Solving cell formation problems in a manufacturing environment with flexible processing and routeing capabilities. International Journal of Production Research, 1996, 34 (10): 2901–2923

    Article  MATH  Google Scholar 

  33. Chiang T, Fu L. Using dispatching rules for job shop scheduling with due date-baesd objectives. International Journal of Production Research, 2007, 45(14): 3245–3262

    Article  MATH  Google Scholar 

  34. Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 2002, 6: 182–197

    Article  Google Scholar 

  35. Wen X, Li X, Gao L, et al. Improved genetic algorithm with external archive maintenance for multi-objective integrated process planning and scheduling. In: Proceedings of IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD). Whistler: IEEE, 2013, 385–390

    Google Scholar 

  36. Baykasoglu A, Ozbakir L. A grammatical optimization approach for integrated process planning and scheduling. Journal of Intelligent Manufacturing, 2009, 20(2): 211–221

    Article  Google Scholar 

  37. Jain A, Jain P, Singh I. An integrated scheme for process planning and scheduling in FMS. International Journal of Advanced Manufacturing Technology, 2006, 30(11–12): 1111–1118

    Article  MathSciNet  Google Scholar 

  38. Li X, Shao X, Gao L, et al. An effective hybrid algorithm for integrated process planning and scheduling. International Journal of Production Economics, 2010, 126(2): 289–298

    Article  Google Scholar 

  39. Lian K, Zhang C, Gao L, et al. Integrated process planning and scheduling using an imperialist competitive algorithm. International Journal of Production Research, 2012, 50(15): 4326–4343

    Article  Google Scholar 

  40. Wong T, Leung C, Mak K, et al. Integrated process planning and scheduling/rescheduling—An agent-based approach. International Journal of Production Research, 2006, 44(18–19): 3627–3655

    Article  MATH  Google Scholar 

  41. Lee S, Moon I, Bae H, et al. Flexible job-shop scheduling problems with ‘AND’/‘OR’ precedence constraints. International Journal of Production Research, 2012, 50(7): 1979–2001

    Article  Google Scholar 

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Correspondence to Muhammad Farhan Ausaf.

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Ausaf, M.F., Gao, L. & Li, X. Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm. Front. Mech. Eng. 10, 392–404 (2015). https://doi.org/10.1007/s11465-015-0353-y

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  • DOI: https://doi.org/10.1007/s11465-015-0353-y

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