Optimisation of integrated process planning and scheduling using a particle swarm optimisation approach

International Journal of Production Research

Volumn 47, Issue 14, 2009, Pages 3775-3796

  Guo, Y W ^a   Li, W D ^b   Mileham, A R ^a   Owen, G W ^a  

^a University of Bath   (United Kingdom)

^b Faculty of Engineering and Computing   (United Kingdom)

Author keywords

Genetic algorithm; Integrated process planning and scheduling; Particle swarm optimisation; Re planning; Simulated annealing

Indexed keywords

INTEGRATED PROCESS PLANNING AND SCHEDULING; JOB PERFORMANCE; JOB SHOP; LOCAL OPTIMA; MACHINE BREAKDOWN; MAKESPAN; MANUFACTURING ENVIRONMENTS; OPTIMISATIONS; PARTICLE SWARM OPTIMISATION; PSO ALGORITHMS; RE-PLANNING; REPRESENTATION MODEL; SEARCH SPACES; SIMULATED ANNEALING ALGORITHMS; TOTAL JOB TARDINESS;

ANNEALING; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS; PROCESS CONTROL; PROCESS PLANNING; RESEARCH; SCHEDULING ALGORITHMS;

SIMULATED ANNEALING;

EID: 70449632611     PISSN: 00207543     EISSN: 1366588X     Source Type: Journal    
DOI: 10.1080/00207540701827905     Document Type: Article

References (25)

1. Aldakhilallah, K.A. and Ramesh, R., 1999. Computer-integrated process planning and scheduling (CIPPS): Intelligent support for product design, process planning and control. International Journal of Production Research, 37 (3), 481-500.
2. Cagnina L., Esquivel, S. and Gallard, R., 2004. Particle swarm optimisation for sequencing problems: A case study. In: 2004 congress on evolution computation (CEC2004), 19-23 September 2004, Portland, USA, 1. IEEE Computational Intelligent Society Press, 536-541.
3. Chang, T.C. and Wysk, R.A., 1985. An introduction to automated process planning systems. Englewood, Cliffs, NJ: Prentice-Hall Inc.
4. Guo, Y.W., Mileham, A.R., Owen, G.W. and Li, W.D., 2006. Operation sequencing optimisation using a particle swarm optimisation approach. In: Proceedings of the institution of mechanical engineers, Journal of Engineering Manufacture, Part B, 220 (B12), 1945-1958.
5. Huang, S.H., Zhang, H.C., and Smith, M.L., 1995. A progressive approach for the integration of process planning and scheduling. IIE Transactions, 1, 456-464.
6. Jerald, J., Asokan, P., Prabaharan, G., and Saravanan, R., 2005. Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm. International Journal of Advanced Manufacturing Technology, 25, 964-971.
7. Kennedy, J. and Eberhart, R., 1995. Particle swarm optimisation. In: Proceedings of the IEEE international conference on neural networks, 27 November-1 December, Perth, Australia, IV. Piscataway, NJ: IEEE Service Centre, 1942-1948.
8. Kim, Y.K., Park, K., and Ko, J., 2003. A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling. Computers & Operations Research, 30, 1151-1171.
9. Li, W.D. and Mcmahon, C.A., 2007. A simulated annealing-based optimisation approach for integrated process planning and scheduling. International Journal of Computer Integrated Manufacturing, 20, 80-95.
10. Li, W.D., Ong, S.K., and Nee, A.Y.C., 2004. Optimisation of process plans using a constraint-based tabu search approach. International Journal of Production Research, 42 (10), 1955-1985.
11. Moon, C., Kim, J., and Hur, S., 2002. Integrated process planning and scheduling with minimising total tardiness in multi-plants supply chain. Computers & Industrial Engineering, 43, 331-349.
12. Moon, C. and Seo, Y., 2005. Evolutionary algorithm for advanced process planning and scheduling in a multi-plant. Computers & Industrial Engineering, 48, 311-325.
13. Morad, N. and Zalzala, A., 1999. Genetic algorithms in integrated process planning and scheduling. Journal of Intelligent Manufacturing, 10, 169-179.
14. Onwubolu, G.C. and Clerc, M., 2004. Optimal path for automated drilling operations by a new heuristic approach using particle swarm optimisation. International Journal of Production Research, 42 (3), 473-491.
15. Pang, W., Wang, K.P, Zhou, C.G. and Dong, L.J., 2004. Fuzzy discrete particle swarm optimisation for solving travelling salesman problem. In: Proceedings of the 4th international conference on computer and information technology (CIT '04), 14-16 September 2004, Wuhan, China. IEEE Computer Society Press, 796-800.
16. Sormaz, D. and Khoshnevis, B., 2003. Generation of alternative process plans in integrated manufacturing systems. Journal of Intelligent Manufacturing, 14, 509-526.
17. Stacey, A., Jancic, M. and Grundy, I., 2003. Particle swarm optimisation with mutation. 2003 Congress on Evolution Computation (CEC2003), 2, 1425-1430.
18. Tan, W. and Khoshnevis, B., 2000. Integration of process planning and scheduling - a review. Journal of Intelligent Manufacturing, 11, 51-63.
19. Tonshoff, H.K., Beckendorff, U. and Andres, N., 1989. FLEXPLAN: A concept for intelligent process planning and scheduling. In: Proceedings of the CIRP International Workshop, 21-22 September, Hannover, Germany. Hannover University, 87-106.
20. Wang, K.P., Huang, L., Zhou, C.G. and Pang, W., 2003. Particle swarm optimisation for travelling salesman problem. In: Proceedings of the 2nd international conference on machine learning and cybernetics, 2-5 November 2003, Xi'an, China. Washington, DC: IEEE Computer Society Press.
21. Wong, T.N., Leung, C.W., Mak, K.L., and Fung, R.Y.K., 2006. An agent-based negotiation approach to integrate process planning and scheduling. International Journal of Production Research, 44 (7), 1331-1351.
22. Yan, H.S., Xia, Q.F., Zhu, M.R., Liu, X.L., and Guo, Z.M., 2003. Integrated production planning and scheduling on automobile assembly lines. IIE Transactions, 35, 711-725.
23. Zhang, F., Zhang, Y.F., and Nee, A.Y.C., 1997. Using genetic algorithms in process planning for job shop machining. IEEE Transactions on Evolutionary Computation, 1 (4), 278-289.
24. Zhang, X.D. and Yan, H.S., 2005. Integrated optimisation of production planning and scheduling for a kind of job-shop. International Journal of Advanced Manufacturing Technology, 26, 876-886.
25. Zhang, Y.F., Saravanan, A.N., and Fuh, J.Y.H., 2003. Integration of process planning and scheduling by exploring the flexibility of process planning. International Journal of Production Research, 41 (3), 611-628.