Expected energy analysis for industrial process planning problem with fuzzy time parameters

Computers and Chemical Engineering

Volumn 35, Issue 12, 2011, Pages 2905-2912

  Tian, Guangdong ^a   Chu, Jiangwei ^b   Liu, Yumei ^a   Ke, Hua ^c   Zhao, Xin ^d   Xu, Guan ^a  

^a JILIN UNIVERSITY   (China)

^b NORTHEAST FORESTRY UNIVERSITY   (China)

^c TONGJI UNIVERSITY   (China)

^d NORTHEAST NORMAL UNIVERSITY   (China)

Author keywords

Energy analysis; Expected value; Fuzzy optimization; Fuzzy simulation; Industrial process planning

Indexed keywords

ENERGY ANALYSIS; EXPECTED VALUE; FUZZY OPTIMIZATION; FUZZY SIMULATION; INDUSTRIAL PROCESSS;

ALGORITHMS; CUSTOMER SATISFACTION; ENERGY UTILIZATION; INDUSTRY; NEURAL NETWORKS; OPTIMIZATION; PROCESS PLANNING;

COMPUTER SIMULATION;

EID: 80053914177     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2011.05.012     Document Type: Article

References (26)

1. Bonfill A., Espuna A., Puigjaner L. Addressing robustness in scheduling batch processes with uncertain operation times. Industrial & Engineering Chemistry Research 2005, 44(5):1524-1534.
2. Bottcher J., Drexl A., Kolisch R., Salewski F. Project scheduling under partially renewable resource constraints. Management Science 1999, 45(4):543-559.
3. Charnes A., Cooper W.W., Thompson G.L. Critical path analysis via chance constrained and stochastic programming. Operations Research 1964, 12:460-470.
4. Choi S.H. Fast and robust extraction of optical and morphological properties of human skin using a hybrid stochastic-deterministic algorithm: Monte-Carlo simulation study. Lasers in Medical Science 2010, 25(5):733-741.
5. Eshtehardian E., Afshar A., Abbasnia R. Fuzzy-based MOGA approach to stochastic time-cost trade-off problem. Automation in Construction 2009, 18:692-701.
6. Gao J.W., Liu B. Fuzzy multilevel programming with a hybrid intelligent algorithm. Computers & Mathematics with Applications 2005, 49:1539-1548.
7. Guterrez-Antonio C., Briones-Ramirez A., Jimenez-Gutierrez A. Optimization of Petlyuk sequences using a multi objective genetic algorithm with constraints. Computers & Chemical Engineering 2011, 35(2):236-244.
8. Herroelen W., De Reyck B., Demeulemeester E. Resource constrained project scheduling: A survey of recent developments. Computers & Operations Research 1998, 25(4):279-302.
9. Huang X.X. Credibility-based chance-constrained integer programming models for capital budgeting with fuzzy parameters. Information Science 2006, 176:2698-2712.
10. Kaufmann A., Gupta M.M. Fuzzy mathematical models in engineering and management science 1988, Amsterdam, New York. 1st ed.
11. Kelley J.E. Critical path planning and scheduling, mathematical basis. Operational Research 1961, 9(3):296-320.
12. Kelley J.E. The critical path method: Resources planning and scheduling 1963, Englewood Cliffs, Prentice-Hall. 1st ed.
13. Ke H., Liu B. Fuzzy project scheduling problem and its hybrid intelligent algorithm. Applied Mathematical Modelling 2010, 34:301-308.
14. Ke H., Ma W.M., Gao X., Xu W.H. New fuzzy models for time-cost trade-off problem. Fuzzy Optimization and Decision Making 2010, 9:219-231.
15. Kolisch R., Padman R. An integrated survey of deterministic project scheduling. Omega 2001, 29(3):249-272.
16. Laslo Z., Golenko-Ginzburg D., Keren B. Optimal booking of machines in a virtual job-shop with stochastic processing times to minimize total machine rental and job tardiness costs. International Journal of Production Economics 2008, 111(2):812-821.
17. Li Z.K., Ierapetritou M. Process scheduling under uncertainty: Review and challenges. Computers & Chemical Engineering 2008, 32:715-727.
18. Li J., Gao B. On chance maximization model in fuzzy random decision systems. Mathematical and Computer Modelling 2009, 50:453-464.
19. Liu B. Theory and practice of uncertain programming 2002, Physica-Verlag, Heidelberg. 1st ed.
20. Liu B., Liu Y.K. Expected value of fuzzy variable and fuzzy expected value models. IEEE Transactions on Fuzzy Systems 2002, 10(4):445-450.
21. Liu B. Uncertainty theory: An introduction to its axiomatic foundations 2004, Springer-Verlag, Berlin. 1st ed.
22. Nascimento C.A.O., Giudici R., Guardani R. Neural network based approach for optimization of industrial chemical processes. Computers & Chemical Engineering 2000, 24:2303-2314.
23. Qin R., Liu Y.K. Modeling data envelopment analysis by chance method in hybrid uncertain environments. Mathematics and Computers in Simulation 2010, 80:922-950.
24. Yuan G.Q., Zhao L., Meng M.Q. A new class of two-stage expected value model with fuzzy parameters. Proceedings of the 2009 International Conference on Machine Learning and Cybernetics 2009, 1-6:515-519.
25. Yuan Q., Qian F. A hybrid genetic algorithm for twice continuously differentiable NLP problems. Computers & Chemical Engineering 2010, 34:36-41.
26. Zadeh L. Fuzzy sets. Information and Control 1965, 8:338-353.