Document Type : Original Article

Author

Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, G.C., Tehran, Iran.

Abstract

Aggregate production planning (APP) determines the optimal production plan for the medium term planning horizon. The purpose of the APP is effective utilization of existing capacities through facing the fluctuations in demand. Recently, fuzzy approaches have been applied for APP focusing on vague nature of cost parameters. Considering the importance of coping with customer demand in different periods at different and variable rates, in this research, demand is considered fuzzy and the APP decisions modeled through a bi-objective LP model optimizing production and workforce level costs. The APP decisions are taken in two rounds, First The fuzzy model is transformed to a crisp goal programming counterpart and in the second round as the principal contribution of this paper, the APP decisions for rest of the horizon are updated based on actual demand occurred during starting periods. By generating several sample problems and using the Lingo, the validity of the proposed model is shown.

Keywords

Aghezzaf, E., Khatab, A., and Tam, P. L., (2016). “Optimizing production and imperfect preventive maintenance planning’s integration in failure – prone manufacturing systems”, Reliability Engineering & System Safety, Vol. 145, pp. 190–198, doi: 10.1016/j.ress.2015.09.017
Aliev, R.A., Fazlollahi, B., Guirimov, B.G., and Aliev, R.R., (2007). “Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management”, Information Sciences, Vol. 177, No. 20, pp. 4241-4255, doi: 0.1016/j.ins.2007.04.012
Altendorfer, K., T., Felberbauer, and H., Jodlbauer. (2016). “Effects of Forecast Errors on Optimal Utilization in Aggregate Production Planning with Stochastic Customer Demand”, International Journal of Production Research, Vol. 54, No. 12, pp. 3718–35,  doi:10.1080/00207543.2016.1162918
Baykasoglu, A., and Gocken, T., (2010). “Multi-objective aggregate production planning with fuzzy parameters”, Advances in Engineering Software, Vol. 41, pp. 1124-1131, doi: 10.1016/j.advengsoft.2010.07.002
Bellman, R. E., and Zadeh, L. A., (1970). “Decision-Making in a fuzzy environment”, Management Science, pp. 141-164, doi:10.1287/mnsc.17.4.B141
Chen, L. H., and Tsai, F. C., (2001). Fuzzy goal programming with different importance and priorities, European Journal of Operational Research, 133, 548-556. DOI: 10.1016/S0377-2217(00)00201-0.
Entezaminia, A, Heidari, M, and Rahmani, D, (2017). “Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study”, Int J Adv Manuf Technol, Vol. 90, pp. 1507–1528, doi: 10.1007/s00170-016-9459-6
Entezaminia, A, Heydari, M, and Rahmani, D, (2016). “A Multi-objective Model for Multi-product Multi-site Aggregate Production Planning in a Green Supply Chain: Considering Collection and Recycling Centers”, Journal of Manufacturing Systems, Vol. 40, No. 1, pp. 63–75, doi:10.1016/j.jmsy.2016.06.004
Ghasemy, Y. R., Torabi, S. A., and Fatemi Ghomi, S. M. T., (2012). “Integrated markdown pricing and aggregate production planning in a two echelon supply chain: A hybrid fuzzy multiple objective approach”, Applied Mathematical modelling, Vol. 36, pp. 6011-6030, doi: 10.1016/j.apm.2012.01.029
Gholamian, N, Mahdavi, I, and Tavakkoli-Moghaddam, R, (2016). “Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimization”, International Journal of Computer Integrated Manufacturing, Vol. 29, No. 2, pp. 149–165, doi: 10.1080/0951192X.2014.1002811
Hu, C-F., Teng, C-J., and Li, S-Y., (2007). “A fuzzy goal programming approach to multi-objective optimization problem with priorities”, European Journal of Operational Research, Vol. 176, No. 3, pp. 1319-1333. doi: 10.1016/j.ejor.2005.10.049
Iris C., and Cevikcan E., (2014), “A Fuzzy Linear Programming Approach for Aggregate Production Planning”. In: Kahraman C., Öztayşi B. (eds) Supply Chain Management Under Fuzziness, Studies in Fuzziness and Soft Computing, Vol. 313. Springer, Berlin, Heidelberg, doi: 10.1007/978-3-642-53939-8
Jabbarzadeh, A., Haughton, M., and Pourmehdi F., (2018). “A robust optimization model for efficient and green supply chain planning with postponement strategy”, International Journal of Production Economics,(Article in press), doi:10.1016/j.ijpe.2018.06.013
Jamalnia, A., (2017). “Evaluating the performance of aggregate production planning strategies under uncertainty”, Ph.D. thesis, The University of Manchester Library
Jamalnia, A., and Soukhakian, M. A., (2009). “A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning”, Computers & Industrial Engineering, Vol. 56, pp. 1474-1486, doi: 10.1016/j.cie.2008.09.010
Johnson, Lynwood A., and Montgomery, Douglas C., (1974). Operations research in production planning scheduling and inventory control, John Willy & Sons Inc.
Khemiri, R., Elbedoui-Maktouf, K., Grabot B., and Zouari, B., (2017). “A fuzzy multi-criteria decision-making approach for managing performance and risk in integrated procurement–production planning”, International Journal of Production Research, doi: 10.1080/00207543.2017.1308575
Liou, T. S., and Wang, M. T., (1992). “Ranking fuzzy numbers with integral value”, Fuzzy Sets and Systems, Vol. 50, pp. 247-255, doi: 10.1016/0165-0114(92)90223-Q
Madadi, N, and Wong, KY, (2014). “A multiobjective fuzzy aggregate production planning model considering real capacity and quality of products”, Mathematical Problems in Engineering, pp. 1–15, doi: 10.1155/2014/313829
Makui, A., Heydari, M., Aazami, A., and Dehghani, E., (2016). “Accelerating Benders decomposition approach for robust aggregate production planning of products with a very limited expiration date”, Computers & Industrial Engineering, Vol. 100, pp. 34-51, doi: 10.1016/j.cie.2016.08.005
Modarres, M., and Izadpanahi, E., (2016). “Aggregate production planning by focusing on energy saving: A robust optimization approach”, Journal of Cleaner Production, Vol. 133, pp. 1074-1085, doi:10.1016/j.jclepro.2016.05.133
Narasimhan, R., (1980). “Goal Programming in a Fuzzy Environment”, Decision Science, Vol. 11, pp. 325-336, doi: 10.1111/j.1540-5915.1980.tb01142.x
Nobari, A., Khierkhah, A., and Hajipour, V., (2018). “A Pareto-based approach to optimise aggregate production planning problem considering reliable supplier selection”, International Journal of Services and Operations Management, Vol. 29, No. 1, pp.59–84, doi:  10.1504/IJSOM.2018.088473
Ramezanian, R., Rahmani, D., and Barzinpour, F., (2012). “An aggregate production planning model for two phase production systems: Solving with genetic algorithm and tabu search”, Expert Systems with Applications, Vol. 39, pp. 1256-1263, doi:10.1016/j.eswa.2011.07.134
Taghizadeh, K., Bagherpour, M., and Mahdavi, I., (2011). “Application of Fuzzy Multi-Objective Linear Programming Model in a Multi-Period Multi- Product Production Planning Problem”, International Journal of Computational Intelligence Systems, Vol. 4, No. 2, pp. 228-243, doi: 10.1080/18756891.2011.9727779
Vogel, T., Almada-Lobo, B., and Almeder, C., (2017). “Integrated versus hierarchical approach to aggregate production planning and master production scheduling”, OR Spectrum , Vol. 39, No. 1, pp. 193–229, doi: 10.1007/s00291-016-0450-2
Wang, R.C, and Fang, H. H., (2001). “Aggregate Production Planning With multiple objectives in a fuzzy environment”, European journal of Operational Research, Vol. 133, pp. 521-536, doi: 10.1016/S0377-2217(00)00196-X
Wang, R. C., and Liang, T. F., (2004). “Application of fuzzy multi-objective linear programming to aggregate production planning”, Computers & Industrial Engineering, Vol. 46, pp. 17–41, doi: 0.1016/j.cie.2003.09.009
Zaidan, A.A., Atiya, B., Abu Bakar, M.R., and Zaidan, B.B., (2017). “A new hybrid algorithm of simulated annealing and simplex downhill for solving multiple-objective aggregate production planning on fuzzy environment”, Neural Computations & Applications, doi: 10.1007/s00521-017-3159-5
Zhu, B., Hui, J., Zhang, F., and He, L., (2018). “An Interval Programming Approach for Multi-period and Multi-product Aggregate Production Planning by Considering the Decision Maker’s Preference”, International Journal of Fuzzy Systems , Vol. 20, No. 3, pp. 1015–1026, doi: 10.1007/s40815-017-0341-y
Zimmermann, H.J., (1978). “Fuzzy programming and linear programming with several objective functions”, Fuzzy Sets and Systems, Vol. 1, pp. 45–56, doi: 10.1016/0165-0114(78)90031-3