Solving Machine Loading Problem in Flexible Manufacturing Systems Using Particle Swarm Optimization
Commenced in January 2007
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Edition: International
Paper Count: 32797
Solving Machine Loading Problem in Flexible Manufacturing Systems Using Particle Swarm Optimization

Authors: S. G. Ponnambalam, Low Seng Kiat

Abstract:

In this paper, a particle swarm optimization (PSO) algorithm is proposed to solve machine loading problem in flexible manufacturing system (FMS), with bicriterion objectives of minimizing system unbalance and maximizing system throughput in the occurrence of technological constraints such as available machining time and tool slots. A mathematical model is used to select machines, assign operations and the required tools. The performance of the PSO is tested by using 10 sample dataset and the results are compared with the heuristics reported in the literature. The results support that the proposed PSO is comparable with the algorithms reported in the literature.

Keywords: Machine loading problem, FMS, Particle Swarm Optimization.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1075605

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References:


[1] Tiwari M.K., Vidyarthi N.K., "Solving machine loading problem in flexible manufacturing system using genetic algorithm based heuristic approach", International Journal of Production Research, vol. 38, no. 14, pp. 3357-84, 2000.
[1] Swarnkar.R, and Tiwari.M.K, "Modeling machine loading problem of FMSs and its solution methodology using a hybrid tabu search and simulated annealing based heuristic approach", Robotics and Computer Integrated Manufacturing , vol. 20, pp. 199-209, 2003.
[2] Prakash, A., Nitesh Khilwani, Tiwari M.K. and Yuval Cohen, "Modified Immune Algorithm for job selection and operation allocation problem in Flexible Manufacturing Systems", Advances in Engineering Software, vol. 39, no. 3, pp. 219-232, 2008.
[4] Chan F.T.S., Swamkar R. and Tiwari M.K., 2005, Fuzzy goalprogramming model with an artificial immune system (AIS) approach for a machine tool selection and operation allocation problem in a flexible manufacturing system, International Journal of Production Research, vol. 43, no. 19, pp. 4147-4163.
[5] Tripathi A.K. and Tiwari M.K., Chan F.T.S., "Multi-agent-based approach to solve part section and task allocation problem in flexible manufacturing systems", International Journal of Production Research, vol. 43, no. 7, pp. 1313-1335, 2005.
[6] Akhilesh Kumar, Prakash, M. K. Tiwari, Ravi Shankar, and Alok Baveja, "Solving machine-loading problem of a flexible manufacturing system with constrained-based genetic algorithm", European Journal of Operational Research, vol. 175, no. 2, pp. 1043-1069, 2006.
[7] Yogeswaran, M.; Ponnambalam, S.G.; Tiwari, M.K, "An hybrid evolutionary heuristic using genetic algorithm and simulated annealing algorithm to solve machine loading problem in FMS", International Journal of Production Research, in-print, 2008.
[8] J. Kennedy, R. Eberhart and Y. Shi, Swarm Intelligence, Morgan Kaufmann, San Mateo, CA, USA, 2001.
[9] Varadharajan, T. K., and Rajendran, C, A multi-objective simulatedannealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs, European Journal of Operational Research, vol. 167, no. 3, pp. 772-795, 2005.
[10] Chandrasekaran, S, Ponnambalam, S. G, Suresh, R. K, "Multi-objective particle swarm optimization algorithm for scheduling in flowshops to minimize makespan, total flowtime and completion time variance,", Proceedings of IEEE International Congress on Evolutionary Computation 2007, IEEE CEC 2007, Singapore, September 25-28, 2007, pp. 4012-4018.
[11] Shankar,K., and Srinivasulu,A., "Some solution methodologies for loading problems in flexible manufacturing system", International Journal of Production Research, vol. 27, no. 6, pp. 1019-1034, 1989.
[12] Mukhopadhyay S. K, Midha S, Murlikrishna, V., "A heuristic procedure for loading problem in flexible manufacturing systems", International Journal of Production Research, vol. 30, no. 9, pp. 2213-28, 1992.
[13] Tiwaii,M. K., Hazarika, B., Vidyarthi, N. K., Jaggi, P., and Mukhopadhyay, S. K., "A heuristic solution to machine loading problem of a FMS and its Petri net model", International Journal of Production Research, vol. 35, no. 8, pp. 2269-2284, 1997.
[14] Vidyarthi N.K and Tiwari M.K., "Machine loading problem of FMS: a fuzzy-based heuristic approach", International Journal of Production Research, vol. 39, no. 5, pp. 953-979, 2001.
[15] Srinivas, Tiwari, M. K. and Allada, V., "Solving the machine loading problem in a flexible manufacturing system using a combinatorial auction-based approach", International Journal of Production Research, vol. 42, no. 9,pp. 1879-1893, 2004.
[16] Kumar, R.R., Amarjit Kumar Singh and Tiwari,M.K., "A fuzzy based algorithm to solve the machine-loading problems of a-FMS.and its neuro fuzzy Petri net model", International Journal of Advanced Manufacturing Technology, vol. 23, no. (5¬6), pp. 318-341, 2004.
[17] Nagarjuna, N., Mahesh, and Rajagopal,K., "A heuristic based on multistage programming approach for machine loading problem in a flexible manufacturing system", Robotics and Computer Integrated Manufacturing, vol. 22, no. 4, pp. 342-352, 2006.