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A planning model for the chemical integrated system under uncertainty by grey programming approach

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A model to optimize the planning of the chemical integrated system comprised by multi-devices and multi-products has been proposed in this paper. With the objective to make more profits, the traditional model for optimizing production planning has been proposed. The price of chemicals, the market demand, and the production capacity have been considered as mutative variables, then an improved model in which some parameters are not constant has been developed and a new method to solve the grey linear programming has been proposed. In the grey programming model, the value of credibility can be suggested by the decision-makers, and the results of the production planning calculated by the model can help them to achieve their desired target. An actual case has been studied by the proposed methodology, and the proposed methodology can be popularized to other cases.
Rocznik
Strony
16--22
Opis fizyczny
Bibliogr. 32 poz., rys., tab.
Twórcy
autor
  • School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
  • CESQA (Quality and Environmental Research Centre), University of Padova, Department of Industrial Engineering, Via Marzolo 9, 35131 Padova, Italy
autor
  • School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
autor
  • School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
autor
  • School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
autor
  • School of Chemistry and Chemical Engineering, Chongqing University, Chongqing 400044, China
autor
  • Laboratoire PRiSM, Université de Versailles Saint-Quentin en Yvelines, 45 Avenue des Etats-Unis, 78035 Versailles Cedex, France
Bibliografia
  • 1. Xie, J.P., Kong, L.C. & Ji, W. (2009). The industrial Development Mode of Chemical Industry Parks--Take the Industry Parks in Yangtze River Delta as an Example. Journal of Shijiazhuang University of Economics 32 (1), 8-13, in Chinese.
  • 2. Liu, Q., Li, H.M., Zuo, X.L., Zhang, F.F. & Wang, L. (2009). A survey and analysis on public awareness and performance for promoting circular economy in China: A case study from Tianjin. Journal of Cleaner Production 17 (2): 265-270. DOI: 10.1016/j.jclepro.2008.06.003.
  • 3. Geng, Y., Fu, J., Sarkis, J. & Xue, B. (2012) . Towards a national circular economy indicator system in China: an evaluation and critical analysis. Journal of Cleaner Production 23 (1): 216-224. DOI: 10.1016/j. jclepro.2011.07.005.
  • 4. Chen, J.W. (2008). Efficient use of crude oil resource by integration of oil refining and chemical production. Modern Chemical Industry 24 (8),1-5, in Chinese.
  • 5. Shentu, L.V. (1999). On the Mergingly Developing Trend of Refining and Petrochemical. Guangdong Chemical Industry 3, 21-22, in Chinese.
  • 6. Wu, J.Y., He, X.R., Qiu T. & Chen, B.Z. (2002). A Quanratic Programming Model of Production Planning with Changeable Cost for Refinery. Petroleum Processing and Petrochemicals 33 (9),49-51, in Chinese.
  • 7. Pinar, M.C. (2000). A simple duality proof in convex quadratic programming with a quadratic constraint, and some applications. European Journal of Operational Research 124 (1): 152-158. DOI: 10.1016/ S0377-2217(99)00173-3.
  • 8. Ammar, E.E. (2007). On solutions of fuzzy random multiobjective quadratic programming with application in portfolio problem. Information Science 178 (2): 468-484. DOI: 10.1016/j.ins.2007.03.029.
  • 9. Ammar, E.E. (2009). On fuzzy random multiobjective quadratic programming. European Journal of Operational Research 193 (2): 329-341. DOI: 10.1016/j. ins.2007.03.029.
  • 10. Zeng, M.G., Yin, Q.H., Xie, X.A. & Hua, B. (2002). Modeling and Optimization of Multi-refineries’ Production Planning Based on Regional Resources Optimal Dispostion. Petroleum Refinery Engineering 32 (5), 31-34, in Chinese.
  • 11. Lu, W.C., Wang, Z., Chai, X.F. & Wang, H. (2008). Study on Application of Multi-plant Production Planning Optimization Model. Technology & Economics in Perochemical 24 (6), 18-22, in Chinese.
  • 12. You, F.Q. & Grossmann, I.E. (2008). Design of responsive supply chains under demand uncertainty. Computers and Chemical Engineering 32, 3090-3111. DOI: 10.1016/j.compchemeng.2008.05.004.
  • 13. Gao, J.Z. (2004). Drift of The Optimal Solutions and Optima of a Grey Lineat Program.Journal of Shangdong Normal University (Nutral Science) 19 (2),1-3, in Chinese.
  • 14. Gumus, A.T., Guneri, A.F. & Keles, S. (2009). Supply chain network design using an integrated neuro- fuzzy and MILLP approach: A comparative dedign study. Expert Systems with Applications 36,12570-12577. DOI: 10.1016/j.eswa.2009.05.034.
  • 15. Liang, R.H. (1997). Application of grey linear programming to short-term hydro scheduling. Electric Power Systems Research 41 (3): 159-165. DOI: 10.1016/ S0378-7796(96)01128-5.
  • 16. Li, Q.X. & Liu, S.F. (2008). The foundation of the grey matrix and the grey input-output analysis. Applied Mathematical Modelling 32, 267-291. DOI: 10.1016/j. apm.2006.12.002.
  • 17. Li S.J., Lin, H.B. & Yang, Y.R. (2002). Application of Fuzzy Progtamming for Optimization of Refinery Productioon Planning. Acta Petroleisinica(Petroleum Processing Section),18(1), 78-83, in Chinese.
  • 18. Mahdavi-Amirim, N. & Nasseri, S.H. (2007). Duality results and a dual simplex method for linear programming problems with trapezoidal fuzzy variables. Fuzzy Sets and Systems 158 (17): 1961-1978. DOI: 10.1016/j. fss.2007.05.005.
  • 19. Ravi, V. & Reddy, P.J. (1998). Fuzzy linear fractional goal programming applied to refinery operations planning. Fuzzy Sets and Systems 96 (2): 173-182. DOI: 10.1016/S0165-0114(96)00294-1.
  • 20. Lee, C.S. & Wen, C.G. (1996). River assimilative capacity analysis via fuzzy linear programming. Fuzzy Sets and Systems 79 (2): 191-201. DOI: 10.1016/0165-0114(95)00171-9.
  • 21. Dubey, D., Chandra, S. & Mehra, A. (2012). Fuzzy linear programming under interval uncertainty based on IFS representation. Fuzzy Sets and Systems 188 (1): 68-87. DOI: 10.1016/j.fss.2011.09.008.
  • 22. Saad, O.M. (1995). Stability on multiobjective linear programming problems with fuzzy parameters. Fuzzy Sets and Systems 74 (2): 207-215. DOI: 10.1016/0165-0114(94)00334-4.
  • 23. Yan, X.Z. & Song, Z.M. (2002). Grey Linear Programming and Its Solving Approach. Journal of Yantai University (Natural Science and Engineering Edition) 15 (2), 104-108, in Chinese.
  • 24. Huang, G.H., Baetz, B.W. & Patry, G.G. (1995). Grey integer programming: An application to waste management planning under uncertainty. European Journal of Operational Research 83 (3): 594-620. DOI: 10.1016/0377-2217(94)00093-R.
  • 25. Galvez, E.D., Cisternas, L.A., Patino, P.S., Ossandon, K.L. (2008). Application of grey programming to process design. Computer Aided Chemical Engineering 25: 671-676. DOI: 10.1016/S1570-7946(08)80117-4.
  • 26. Chang, N.B., Wen, C.G., Chen, Y.L. & Yong, Y.C. (1996). A grey fuzzy multiobjective programming approach for the optimal planning of a reservoir watershed. Part A: Theoretical Development. Water Research 30 (10): 2329-2334. DOI: 10.1016/0043-1354(96)00124-8.
  • 27. Davila, E., Chang, E.B. & Diwakaruni, S. (2005). Landfill space consumption dynamics in the Lower Rio Grande Valley by grey integer programming-based games. Journal of Environmental Management. 75 (4): 353-365. DOI: 10.1016/j.jenvman.2004.11.015.
  • 28. Ko, A.S. & Chang, N.B. (2008). Optimal planning of co-firing alternative fuels with coal in a power plant by grey nonlinear mixed integer programming model. Journal of Environmental Management 88 (1): 11-27. DOI: 10.1016/j.jenvman.2007.01.021.
  • 29. Hsu, C.I. & Wen, Y.H. (2000). Application of grey theory and multiobjective programming towards airline network design. European Journal of Operational Research 127 (1): 44-68. DOI: 10.1016/S0377-2217(99)00320-3.
  • 30. Luo, D. & Lu, S.F. (2004). On the Algorithm of Grey Multiple Objective Programming. Systems Engineering 22 (6), 12-15, in Chinese.
  • 31. Liao, C.L. (2001). Grey Linear Programming in the Regional Sales Design. Journal of Chongqing University (Natural Science Edition) 24 (3): 124-126, in Chinese.
  • 32. Bi, Y.M., Li, J.W. & Li, G.M. (1999). Genocop Algorithm for Solving Gray Linear Programming Problem. Systems Engineering and Electronics 21(10): 38-40, in Chinese.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-952b956b-4525-4d5d-94ff-c929a6dd6cf8
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