IDEAS home Printed from https://ideas.repec.org/r/eee/proeco/v98y2005i3p328-341.html

Applying possibilistic linear programming to aggregate production planning

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Sina Abbasi & Sobhan Jabari & Akram Mirzaei & Ashkan Azimi azad & Saba Zamanian, 2025. "Using a Just‐In‐Time Approach in the Green Supply Chain, Taking Into Account CO2 Emissions, Under Uncertainty in the Pre‐ and Post‐COVID‐19 Situation," Discrete Dynamics in Nature and Society, John Wiley & Sons, vol. 2025(1).
  2. Rosso-Cerón, A.M. & Kafarov, V. & Latorre-Bayona, G. & Quijano-Hurtado, R., 2019. "A novel hybrid approach based on fuzzy multi-criteria decision-making tools for assessing sustainable alternatives of power generation in San Andrés Island," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 159-173.
  3. Zhang, Xiaodong & Huang, Guo H. & Nie, Xianghui, 2009. "Optimal decision schemes for agricultural water quality management planning with imprecise objective," Agricultural Water Management, Elsevier, vol. 96(12), pages 1723-1731, December.
  4. Figueroa–García, Juan Carlos & Hernández, Germán & Franco, Carlos, 2022. "A review on history, trends and perspectives of fuzzy linear programming," Operations Research Perspectives, Elsevier, vol. 9(C).
  5. Rihab Khemiri & Khaoula Elbedoui-Maktouf & Bernard Grabot & Belhassen Zouari, 2017. "A fuzzy multi-criteria decision making approach for managing performance and risk in integrated procurement-production planning," Post-Print hal-01758604, HAL.
  6. Zhengyang Hu & Viren Parwani & Guiping Hu, 2021. "Closed-Loop Supply Chain Network Design under Uncertainties Using Fuzzy Decision Making," Logistics, MDPI, vol. 5(1), pages 1-16, March.
  7. Andrea Borenich & Peter Greistorfer & Marc Reimann, 2020. "Model-based production cost estimation to support bid processes: an automotive case study," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(3), pages 841-868, September.
  8. R. Ghasemy Yaghin & K. Khalajmehri, 2025. "A new hybrid modeling of sustainable supply chain planning with imprecise data in textile industry," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(9), pages 22435-22473, September.
  9. SakallI, Ümit Sami & Baykoç, Ömer Faruk, 2011. "An optimization approach for brass casting blending problem under aletory and epistemic uncertainties," International Journal of Production Economics, Elsevier, vol. 133(2), pages 708-718, October.
  10. F. Jolai & J. Razmi & N. Rostami, 2011. "A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 547-569, December.
  11. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
  12. Vasant, Pandian M. & Barsoum, Nader N. & Bhattacharya, Arijit, 2008. "Possibilistic optimization in planning decision of construction industry," International Journal of Production Economics, Elsevier, vol. 111(2), pages 664-675, February.
  13. Chunyang Yu & Wei Zhang & Xun Xu & Yangjian Ji & Shiqiang Yu, 2018. "Data mining based multi-level aggregate service planning for cloud manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1351-1361, August.
  14. Behnam Vahdani & Meghdad Salimi & Seyed Meysam Mousavi, 2017. "A New Compromise Solution Model Based on Dantzig–Wolfe Decomposition for Solving Belief Multi-Objective Nonlinear Programming Problems with Block Angular Structure," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 333-387, March.
  15. Chui-Yu Chiu & Yi Lin & Ming-Feng Yang, 2014. "Applying Fuzzy Multiobjective Integrated Logistics Model to Green Supply Chain Problems," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
  16. Mirzapour Al-e-hashem, S.M.J. & Malekly, H. & Aryanezhad, M.B., 2011. "A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty," International Journal of Production Economics, Elsevier, vol. 134(1), pages 28-42, November.
  17. Cunico, Maria Laura & Flores, Julio Rolando & Vecchietti, Aldo, 2017. "Investment in the energy sector: An optimization model that contemplates several uncertain parameters," Energy, Elsevier, vol. 138(C), pages 831-845.
  18. Yasser A. Davizón & César Martínez-Olvera & Rogelio Soto & Carlos Hinojosa & Piero Espino-Román, 2015. "Optimal Control Approaches to the Aggregate Production Planning Problem," Sustainability, MDPI, vol. 7(12), pages 1-16, December.
  19. Kabak, Özgür & Ülengin, Füsun, 2011. "Possibilistic linear-programming approach for supply chain networking decisions," European Journal of Operational Research, Elsevier, vol. 209(3), pages 253-264, March.
  20. Díaz-Madroñero, Manuel & Peidro, David & Mula, Josefa & Ferriols, Francisco J., 2010. "Enfoques de programación matemática fuzzy multiobjetivo para la planificación operativa del transporte en una cadena de suministro del sector del automóvil = Fuzzy Multiobjective Mathematical Programming Approaches for Operational Transport Planning ," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 9(1), pages 44-68, June.
  21. Chia-Nan Wang & Thanh-Tuan Dang & Tran Quynh Le & Panitan Kewcharoenwong, 2020. "Transportation Optimization Models for Intermodal Networks with Fuzzy Node Capacity, Detour Factor, and Vehicle Utilization Constraints," Mathematics, MDPI, vol. 8(12), pages 1-27, November.
  22. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
  23. Shih-Pin Chen & Wen-Lung Huang, 2014. "Solving Fuzzy Multiproduct Aggregate Production Planning Problems Based on Extension Principle," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2014, pages 1-18, August.
  24. Paramanik, Arup Ratan & Mahanty, Biswajit, 2025. "A collaborative circular supply chain network design framework for implementing individual producer responsibility under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 203(C).
  25. Shahparvari, Shahrooz & Abbasi, Babak & Chhetri, Prem, 2017. "Possibilistic scheduling routing for short-notice bushfire emergency evacuation under uncertainties: An Australian case study," Omega, Elsevier, vol. 72(C), pages 96-117.
  26. Nadi Serhan Aydin & Erfan Babaee Tirkolaee, 2025. "A systematic review of aggregate production planning literature with an outlook for sustainability and circularity," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(10), pages 23161-23202, October.
  27. Mula, Josefa & Peidro, David & Poler, Raul, 2010. "The effectiveness of a fuzzy mathematical programming approach for supply chain production planning with fuzzy demand," International Journal of Production Economics, Elsevier, vol. 128(1), pages 136-143, November.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.