Production Optimization on the Flow Shop Scheduling Problem: A Simulation Study
Subject Areas :Farshid Salehi 1 , Seyed Mojtaba Sajadi 2 , Mohammad Mehdi Karami 3
1 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Faculty of Entrepreneurship, New Business Department, University of Tehran, Iran
3 - Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
Keywords:
Abstract :
[1] Bon, A.T. and Shahrin, N.N. 2016. Assembly Line Optimization using Arena Simulation. Proceedings of the International Conference on Industrial Engineering and Operations Management Kuala Lumpur, Malaysia. March 8-10.
[2] Dantzig, G.B. and Ramser, J.H. 1959. The truck dispatching problem. Management Science. 6(1): 80-91.
[3] Gutjahr, A.L. and Nemhauser, G.L. 1964. An algorithm for the line balancing problem. Management science. 11(2):308-315.
[4] Papavasileiou, V., Koulouris, A., Siletti, C. and Petrides, D. 2007. Optimize manufacturing of pharmaceutical products with process simulation and production scheduling tools. Chemical Engineering Research and Design. 85(7):1086-1097.
[5] Petrides, D., Carmichael, D., Siletti, C. and Koulouris, A. 2014. Biopharmaceutical process optimization with simulation and scheduling tools. Bioengineering. 1(4): 154-187.
[6] Kulkarni, K. and Venkateswaran, J. 2015. Hybrid approach using simulation-based optimisation for job shop scheduling problems. Journal of Simulation. 9(4): 312-324.
[7] Kaylani, H. and Atieh, A.M. 2016. Simulation approach to enhance production scheduling procedures at a pharmaceutical company with large product mix. Procedia Cirp. 41:411-416.
[8] Alrabghi, A., Tiwari, A. and Savill, M. 2017. Simulation-based optimisation of maintenance systems: Industrial case studies. Journal of Manufacturing Systems. 44: 191-206.
[9] Pourhassan, M.R. and Raissi, S. 2017. An integrated simulation-based optimization technique for multi-objective dynamic facility layout problem. Journal of Industrial Information Integration. 8: 49-58.
[10] Almasarwah, N. and Süer, G. 2018. Product Scheduling in a Flowshop Cell. Procedia Manufacturing. 17: 206-213.
[11] Mendes, A.A. and Lorenzoni, M.W. 2018. Analysis and optimization of periodic inspection intervals in cold standby systems using Monte Carlo simulation. Journal of manufacturing systems. 49: 121-130.
[12] Sadegh, S., Sajadi, S.M., and Fariborz, J. 2018. A Simulation-based optimization model for determining the sequence of implementing projects related to new product development. Journal of Modern Research in Decision Making, 2(4): 129-152.
[13] González-Neira, E.M., Montoya-Torres, J.R. and Caballero-Villalobos, J.P. 2019. A comparison of dispatching rules hybridised with Monte Carlo Simulation in stochastic permutation flow shop problem. Journal of Simulation. 13(2): 128-137.
[14] SajadiAzar, S.M., Alizadeh, A., Zandieh, M. and Tavan, F. 2019. Robust and stable flexible job shop scheduling with random machine breakdowns: multi-objectives genetic algorithm approach. International Journal of Mathematics in Operational Research. 14(2): 268-289.
[15] Aiassi, R., Sajadi, S.M., Hadji-Molana, S. M. and Zamani-Babgohari, A. 2020. Designing a stochastic multi-objective simulation-based optimization model for sales and operations planning in built-to-order environment with uncertain distant outsourcing. Simulation Modelling Practice and Theory. 104: 102103.
[16] Davari, A., Ganji, M. and Sajadi, S.M. 2002. An Integrated simulation-fuzzy model for preventive maintenance optimization in multi-product production firms. Journal of Simulation. Published online: 1-18.
[17] Kelton, W.D., Sadowski, R. and Zupick, N. 2014. Simulation with ARENA. : McGraw-hill. 6th Edition.