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How to cite this paper
APA: Cheraghalikhani, A., Khoshalhan, F & Mokhtari, H. (2019). Aggregate production planning: A literature review and future research directions. International Journal of Industrial Engineering Computations, 10(2), 309-330.
Chicago/Turabian: Cheraghalikhani, A., Khoshalhan, F & Mokhtari, H. 2019. "Aggregate production planning: A literature review and future research directions." International Journal of Industrial Engineering Computations 10, no. 2 (2019): 309-330.
AMA: Cheraghalikhani, A., Khoshalhan, F & Mokhtari, H. Aggregate production planning: A literature review and future research directions. International Journal of Industrial Engineering Computations. 2019;10(2):309-330.
References
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Aghezzaf, E. H., & Artiba, A. (1998). Aggregate planning in hybrid flowshops. International Journal of Production Research, 36(9), 2463-2477.
Aliev, R. A., Fazlollahi, B., Guirimov, B. G., & Aliev, R. R. (2007). Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management. Information Sciences, 177(20), 4241-4255.
Baykasoglu, A. (2001). MOAPPS 1.0: aggregate production planning using the multiple-objective tabu search. International Journal of Production Research, 39(16), 3685-3702.
Baykasoğlu, A., & Göçken, T. (2006). A tabu search approach to fuzzy goal programs and an application to aggregate production planning. Engineering Optimization, 38(2), 155-177.
Baykasoglu, A., & Gocken, T. (2010). Multi-objective aggregate production planning with fuzzy parameters. Advances in Engineering Software, 41(9), 1124-1131.
Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), B-141.
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Chakrabortty, R., & Hasin, M. (2013). Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach. International Journal of Industrial Engineering Computations, 4(1), 1-12.
Chakrabortty, R. K., Hasin, M. A. A., Sarker, R. A., & Essam, D. L. (2015). A possibilistic environment based particle swarm optimization for aggregate production planning. Computers & Industrial Engineering, 88, 366-377.
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Chen, S. P., & Huang, W. L. (2010). A membership function approach for aggregate production planning problems in fuzzy environments. International Journal of Production Research, 48(23), 7003-7023.
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da Silva, C. G., Figueira, J., Lisboa, J., & Barman, S. (2006). An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming. Omega, 34(2), 167-177.
da Silva, A. F., & Marins, F. A. S. (2014). A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill. Energy Economics, 45, 196-204.
Entezaminia, A., Heidari, M., & Rahmani, D. (2017). Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study. The International Journal of Advanced Manufacturing Technology, 90(5-8), 1507-1528.
Entezaminia, A., Heydari, M., & 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, 40, 63-75.
Erfanian, M., & Pirayesh, M. (2016, December). Integration aggregate production planning and maintenance using mixed integer linear programming. In Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on (pp. 927-930). IEEE.
Fahimnia, B., Luong, L. H. S., & Marian, R. M. (2005). Modeling and optimization of aggregate production planning-A genetic algorithm approach. International Journal of Mathematics and Computer Science, 1, 1-6.
Fiasché, M., Ripamonti, G., Sisca, F. G., Taisch, M., & Tavola, G. (2016). A novel hybrid fuzzy multi-objective linear programming method of aggregate production planning. In Advances in Neural Networks (pp. 489-501). Springer, Cham.
Filho, O. S. (1999). An aggregate production planning model with demand under uncertainty. Production Planning & Control, 10(8), 745-756.
Foote, B. L., Ravindran, A., & Lashine, S. (1988). Production planning & scheduling: Computational feasibility of multi-criteria models of production, planning and scheduling. Computers & Industrial Engineering, 15(1-4), 129-138.
Fung, R. Y., Tang, J., & Wang, D. (2003). Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 33(3), 302-313.
Galbraith, J. R. (2007). Designing Complex Organizations (Addison-Wesley series on organization development).
Ganesh, K., & Punniyamoorthy, M. (2005). Optimization of continuous-time production planning using hybrid genetic algorithms-simulated annealing. The International Journal of Advanced Manufacturing Technology, 26(1-2), 148-154.
Gholamian, N., Mahdavi, I., & Tavakkoli-Moghaddam, R. (2016). Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation. International Journal of Computer Integrated Manufacturing, 29(2), 149-165.
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Hahn, G. J., & Brandenburg, M. (2017). A sustainable aggregate production planning model for the chemical process industry. Computers & Operations Research, 94, 154-168.
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Hax, A. C., & Candea, D. (1984). Production and Inventory Management.
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Iris, C., & Cevikcan, E. (2014). A fuzzy linear programming approach for aggregate production planning. In Supply Chain Management Under Fuzziness (pp. 355-374). Springer, Berlin, Heidelberg.
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Jamalnia, A., & Soukhakian, M. A. (2009). A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning. Computers & Industrial Engineering, 56(4), 1474-1486.
Jamalnia, A., & Feili, A. (2013). A simulation testing and analysis of aggregate production planning strategies. Production Planning & Control, 24(6), 423-448.
Jamalnia, A., Yang, J. B., Xu, D. L., & Feili, A. (2017). Novel decision model based on mixed chase and level strategy for aggregate production planning under uncertainty: Case study in beverage industry. Computers & Industrial Engineering, 114, 54-68.
Kumar, S. A., & Suresh, N. (2009). Operations management. New Age International.
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Aliev, R. A., Fazlollahi, B., Guirimov, B. G., & Aliev, R. R. (2007). Fuzzy-genetic approach to aggregate production–distribution planning in supply chain management. Information Sciences, 177(20), 4241-4255.
Baykasoglu, A. (2001). MOAPPS 1.0: aggregate production planning using the multiple-objective tabu search. International Journal of Production Research, 39(16), 3685-3702.
Baykasoğlu, A., & Göçken, T. (2006). A tabu search approach to fuzzy goal programs and an application to aggregate production planning. Engineering Optimization, 38(2), 155-177.
Baykasoglu, A., & Gocken, T. (2010). Multi-objective aggregate production planning with fuzzy parameters. Advances in Engineering Software, 41(9), 1124-1131.
Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management Science, 17(4), B-141.
Buffa, E. S., & Taubert, W. H. (1972). Production-inventory systems planning and control (No. 658.4032 B8).
Buxey, G. (1993). Production planning and scheduling for seasonal demand. International Journal of Operations & Production Management, 13(7), 4-21.
Chakrabortty, R., & Hasin, M. (2013). Solving an aggregate production planning problem by using multi-objective genetic algorithm (MOGA) approach. International Journal of Industrial Engineering Computations, 4(1), 1-12.
Chakrabortty, R. K., Hasin, M. A. A., Sarker, R. A., & Essam, D. L. (2015). A possibilistic environment based particle swarm optimization for aggregate production planning. Computers & Industrial Engineering, 88, 366-377.
Chaturvedi, N. D., & Bandyopadhyay, S. (2015). Targeting aggregate production planning for an energy supply chain. Industrial & Engineering Chemistry Research, 54(27), 6941-6949.
Chaturvedi, N. D. (2017). Minimizing energy consumption via multiple installations aggregate production planning. Clean Technologies and Environmental Policy, 19(7), 1977-1984.
Chauhan, Y., Aggarwal, V., & Kumar, P. (2017, February). Application of FMOMILP for aggregate production planning: A case of multi-product and multi-period production model. In Advances in Mechanical, Industrial, Automation and Management Systems (AMIAMS), 2017 International Conference on (pp. 266-271). IEEE.
Chen, S. P., & Huang, W. L. (2010). A membership function approach for aggregate production planning problems in fuzzy environments. International Journal of Production Research, 48(23), 7003-7023.
Chen, S. P., & Huang, W. L. (2014). Solving fuzzy multiproduct aggregate production planning problems based on extension principle. International Journal of Mathematics and Mathematical Sciences.
da Silva, C. G., Figueira, J., Lisboa, J., & Barman, S. (2006). An interactive decision support system for an aggregate production planning model based on multiple criteria mixed integer linear programming. Omega, 34(2), 167-177.
da Silva, A. F., & Marins, F. A. S. (2014). A Fuzzy Goal Programming model for solving aggregate production-planning problems under uncertainty: A case study in a Brazilian sugar mill. Energy Economics, 45, 196-204.
Entezaminia, A., Heidari, M., & Rahmani, D. (2017). Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study. The International Journal of Advanced Manufacturing Technology, 90(5-8), 1507-1528.
Entezaminia, A., Heydari, M., & 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, 40, 63-75.
Erfanian, M., & Pirayesh, M. (2016, December). Integration aggregate production planning and maintenance using mixed integer linear programming. In Industrial Engineering and Engineering Management (IEEM), 2016 IEEE International Conference on (pp. 927-930). IEEE.
Fahimnia, B., Luong, L. H. S., & Marian, R. M. (2005). Modeling and optimization of aggregate production planning-A genetic algorithm approach. International Journal of Mathematics and Computer Science, 1, 1-6.
Fiasché, M., Ripamonti, G., Sisca, F. G., Taisch, M., & Tavola, G. (2016). A novel hybrid fuzzy multi-objective linear programming method of aggregate production planning. In Advances in Neural Networks (pp. 489-501). Springer, Cham.
Filho, O. S. (1999). An aggregate production planning model with demand under uncertainty. Production Planning & Control, 10(8), 745-756.
Foote, B. L., Ravindran, A., & Lashine, S. (1988). Production planning & scheduling: Computational feasibility of multi-criteria models of production, planning and scheduling. Computers & Industrial Engineering, 15(1-4), 129-138.
Fung, R. Y., Tang, J., & Wang, D. (2003). Multiproduct aggregate production planning with fuzzy demands and fuzzy capacities. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 33(3), 302-313.
Galbraith, J. R. (2007). Designing Complex Organizations (Addison-Wesley series on organization development).
Ganesh, K., & Punniyamoorthy, M. (2005). Optimization of continuous-time production planning using hybrid genetic algorithms-simulated annealing. The International Journal of Advanced Manufacturing Technology, 26(1-2), 148-154.
Gholamian, N., Mahdavi, I., & Tavakkoli-Moghaddam, R. (2016). Multi-objective multi-product multi-site aggregate production planning in a supply chain under uncertainty: fuzzy multi-objective optimisation. International Journal of Computer Integrated Manufacturing, 29(2), 149-165.
GILGEOUS, V. (1989). Modelling realism in aggregate planning: a goal-search approach. The International Journal of Production Research, 27(7), 1179-1193.
Hahn, G. J., & Brandenburg, M. (2017). A sustainable aggregate production planning model for the chemical process industry. Computers & Operations Research, 94, 154-168.
Hax, A.C. (1978). Aggregate Production Planning. in: J. Models and S. Elmaghraby (eds.), Handbook of Operation Research, New York: Van Nostrand Reinhold.
Hax, A. C., & Candea, D. (1984). Production and Inventory Management.
Ho, C. J. (1989). Evaluating the impact of operating environments on MRP system nervousness. The International Journal of Production Research, 27(7), 1115-1135.
Hsieh, S., & Wu, M. S. (2000). Demand and cost forecast error sensitivity analyses in aggregate production planning by possibilistic linear programming models. Journal of Intelligent manufacturing, 11(4), 355-364.
Iris, C., & Cevikcan, E. (2014). A fuzzy linear programming approach for aggregate production planning. In Supply Chain Management Under Fuzziness (pp. 355-374). Springer, Berlin, Heidelberg.
Ismail, M. A., & ElMaraghy, H. (2009). Progressive modeling—An enabler of dynamic changes in production planning. CIRP annals, 58(1), 407-412.
Jamalnia, A., & Soukhakian, M. A. (2009). A hybrid fuzzy goal programming approach with different goal priorities to aggregate production planning. Computers & Industrial Engineering, 56(4), 1474-1486.
Jamalnia, A., & Feili, A. (2013). A simulation testing and analysis of aggregate production planning strategies. Production Planning & Control, 24(6), 423-448.
Jamalnia, A., Yang, J. B., Xu, D. L., & Feili, A. (2017). Novel decision model based on mixed chase and level strategy for aggregate production planning under uncertainty: Case study in beverage industry. Computers & Industrial Engineering, 114, 54-68.
Kumar, S. A., & Suresh, N. (2009). Operations management. New Age International.
Lai, Y. J., & Hwang, C. L. (1992). A new approach to some possibilistic linear programming problems. Fuzzy Sets and Systems, 49(2), 121-133.
Lee, Y. Y. (1990). Fuzzy sets theory approach to aggregate production planning and inventory control. UMI.
Liang, T. F., Cheng, H. W., Chen, P. Y., & Shen, K. H. (2011). Application of fuzzy sets to aggregate production planning with multiproducts and multitime periods. IEEE Transactions on Fuzzy Systems, 19(3), 465-477.
Liang, T. F., & Cheng, H. W. (2011). Multi-objective aggregate production planning decisions using two-phase fuzzy goal programming method. Journal of Industrial & Management Optimization, 7(2), 365-383.
Leung, S. C., Tsang, S. O., Ng, W. L., & Wu, Y. (2007). A robust optimization model for multi-site production planning problem in an uncertain environment. European journal of operational research, 181(1), 224-238.
Leung, S. C. H., Wu, Y., & Lai, K. K. (2006). A stochastic programming approach for multi-site aggregate production planning. Journal of the Operational Research Society, 57(2), 123-132.
Leung*, S. C., & Wu, Y. (2004). A robust optimization model for stochastic aggregate production planning. Production Planning & Control, 15(5), 502-514.
Leung, S. C., Wu, Y., & Lai, K. K. (2003). Multi-site aggregate production planning with multiple objectives: a goal programming approach. Production Planning & Control, 14(5), 425-436.
Leung, S. C., & Chan, S. S. (2009). A goal programming model for aggregate production planning with resource utilization constraint. Computers & Industrial Engineering, 56(3), 1053-1064.
Leung, S. C., & Ng, W. L. (2007). A goal programming model for production planning of perishable products with postponement. Computers & Industrial Engineering, 53(3), 531-541.
Liang, T. F. (2007). Application of interactive possibilistic linear programming to aggregate production planning with multiple imprecise objectives. Production Planning and Control, 18(7), 548-560.
Madadi, N., & Wong, K. Y. (2014). A multiobjective fuzzy aggregate production planning model considering real capacity and quality of products. Mathematical Problems in Engineering, 2014.
Makui, A., Heydari, M., Aazami, A., & Dehghani, E. (2016). Accelerating Benders decomposition approach for robust aggregate production planning of products with a very limited expiration date. Computers & Industrial Engineering, 100, 34-51.
Mazzola, J. B., Neebe, A. W., & Rump, C. M. (1998). Multiproduct production planning in the presence of work-force learning. European Journal of Operational Research, 106(2-3), 336-356.
Mehdizadeh, E., Niaki, S. T. A., & Hemati, M. (2018). A bi-objective aggregate production planning problem with learning effect and machine deterioration: Modeling and solution. Computers & Operations Research, 91, 21-36.
Al-e, S. M. J. M., Aryanezhad, M. B., & Sadjadi, S. J. (2012). An efficient algorithm to solve a multi-objective robust aggregate production planning in an uncertain environment. The International Journal of Advanced Manufacturing Technology, 58(5-8), 765-782.
Mirzapour Al-e-Hashem, S. M. J., Baboli, A., & Sazvar, Z. (2013). A stochastic aggregate production planning model in a green supply chain: Considering flexible lead times, nonlinear purchase and shortage cost functions. European Journal of Operational Research, 230(1), 26-41.
Mosadegh, H., Khakbazan, E., Salmasnia, A., & Mokhtari, H. (2017). A fuzzy multi-objective goal programming model for solving an aggregate production planning problem with uncertainty. International Journal of Information and Decision Sciences, 9(2), 97-115.
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