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A Two-Stage Placement Algorithm with Multi-Objective Optimization and Group Decision Making


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1 Borissova, D., I. Mustakerov. Wind Power Plant Layout Design and Assessment Considering Forbidden Zones for Location of Turbines. - Adv. Modeling and Optimization, Vol. 19, 2017, pp. 29-38.Search in Google Scholar

2 Borissova, D., I. Mustakerov, D. Korsemov. Business Intelligence System via Group Decision Making. - Cybernetics and Information Technologies, Vol. 16, 2016, No 3, pp. 219-229.10.1515/cait-2016-0045Search in Google Scholar

3 Borissova, D., I. Mustakerov. A Generalized Combinatorial Optimization Approach to Wind Power Plant Design. - Cybernetics and Information Technologies, Vol. 10, 2010, No 4, pp. 62-74.Search in Google Scholar

4 Chen, Y., H. Li, B. He, P. Wang, K. Jin. Multi-Objective Genetic Algorithm Based Innovative Wind Farm Layout Optimization Method. - Energ. Convers. Manage., Vol. 105, 2015, pp. 1318-1327.10.1016/j.enconman.2015.09.011Search in Google Scholar

5 Donovan, S. Wind Farm Optimization. - In Proc. of Annual Conference of the Operations Research Society, Wellington, New Zealand, 2005.Search in Google Scholar

6 Donovan, S., G. Nates, H. Waterer, R. Archer. Mixed Integer Programming Models for Wind Farm Design. - In: Workshop on Mixed Integer Programming, Columbia University, New York City, 2008.Search in Google Scholar

7 Du Pont, B., J. Cagan. An Extended Pattern Search Approach to Wind Farm Layout Optimization. - J. Mech. Design., Vol. 134, 2012.10.1115/1.4006997Search in Google Scholar

8 Ehrgott, M. A Discussion of Scalarization Techniques for Multiple Objective Integer Programming. - Ann. Oper. Res., Vol. 147, 2006, pp. 343-360.10.1007/s10479-006-0074-zSearch in Google Scholar

9 Eichfelder, G. Adaptive Scalarization Methods in Multiobjective Optimization. - Springer, Berlin Haidelberg, 2008.10.1007/978-3-540-79159-1Search in Google Scholar

10 Feng, J., W. Z. Shen. Modelling Wind for Wind Farm Layout Optimization Using Joint Distribution of Wind Speed and Wind Direction. - Energies, Vol. 8, 2015, pp. 3075-3092.10.3390/en8043075Search in Google Scholar

11 Feng, J., W. Z. Shen. Solving the Wind Farm Layout Optimization Problem Using Random Search Algorithm. - Renew. Energ., Vol. 78, 2015, pp. 182-192.10.1016/j.renene.2015.01.005Search in Google Scholar

12 Fulop, J. Introduction to Decision Making Methods. Working Paper 05-6, 2005.Search in Google Scholar

13 Gartner Research Methodologies. http://www.gartner.com/technology/research/methodologiesSearch in Google Scholar

14 Genova, K., L. Kirilov, V. Guljashk i. New Reference-Neighbourhood Scalarization Problem for Multiobjective Integer Programming. - Cybernetics and Information Technologies, Vol. 13, 2013, No 1, pp. 104-114.10.2478/cait-2013-0010Search in Google Scholar

15 Grady, S. A., M. Y. Hussaini, M. M. Abdullah. Placement of Wind Turbines Using Genetic Algorithms. - Renew. Energ., Vol. 30, 2005, pp. 259-270.10.1016/j.renene.2004.05.007Search in Google Scholar

16 S. Greco, M. Ehrgott, J. R. Figueira, Eds. Multiple Criteria Decision Snalysis: State of the Art Surveys. New York, Springer Verlag, 2016.10.1007/978-1-4939-3094-4Search in Google Scholar

17 Katic, I., J. Hojstrup, N. O. Jensen. A Simple Model for Cluster Efficiency. - In: Proc. of European Wind Energy Association Conference and Exhibition, 1986, pp. 407-410.Search in Google Scholar

18 Kokash, N. An Introduction to Heuristic Algorithms. 2005.Search in Google Scholar

19 Kuo, J. Y. J., D. A. Romero, C. H. Amon. A Mechanistic Semi-Empirical Wake Interaction Model for Wind Farm Layout Optimization. - Enegry, Vol. 93, 2015, pp. 2157-2165.10.1016/j.energy.2015.10.009Search in Google Scholar

20 Kwong, W.Y., P.Y. Zhang, D. Romero, J. Moran, M. Morgenroth, C. Amon. Multi- Objective Wind Farm Layout Optimization Considering Energy Generation and Noise Propagation with NSGA-II. - J. Mech. Design., Vol. 136, 2014.10.1115/1.4027847Search in Google Scholar

21 Larson, D.,V. Chang. A Review and Future Direction of Agile, Business Intelligence, Analytics and Data Science. - Int. J. Information Management Vol. 36, 2016, pp. 700-710.10.1016/j.ijinfomgt.2016.04.013Search in Google Scholar

22 Marler, R.T., J.S. Arora. Function-Transformation Methods for Multi-Objective Optimization. - Eng. Optimiz., Vol. 37, 2005, pp. 551-570.10.1080/03052150500114289Search in Google Scholar

23 Marler, R.T., J.S. Arora. Survey of Multi-Objective Optimization Methods for Engineering. - Struct. Multidisc. Optim., Vol. 26, 2004, pp. 369-395.10.1007/s00158-003-0368-6Search in Google Scholar

24 Marmidis, G., S. Lazarou, E. Pyrgioti. Optimal Placement of Wind Turbines ina Wind Park Using Monte Carlo Simulation. - Renew. Energ., Vol. 7, 2008, pp. 1455-1460.10.1016/j.renene.2007.09.004Search in Google Scholar

25 Mora, J.C., J.M.C. Baron, J.M.R. Santos, M.B. Payan. An Evolutive Algorithm for Wind Farm Optimal Design. - Neurocomputing, Vol. 70, 2007, pp. 2651-2658.10.1016/j.neucom.2006.05.017Search in Google Scholar

26 Mosetti, G., C. Poloni, B. Diviacco. Optimization of Wind Turbine Positioning in Large Windfarms by Means ofa Genetic Algorithm. - J. Wind. Engand. Ind. Aerod., Vol. 51, 1994, pp. 105-116.10.1016/0167-6105(94)90080-9Search in Google Scholar

27 Mustakerov, I, D. Borissov a. Wind Turbines Type and Number Choice Using Combinatorial Optimization. - Renew. Energ., Vol. 35, 2010, pp. 1887-1894.10.1016/j.renene.2009.12.012Search in Google Scholar

28 Ostergaard, P. A. Reviewing Optimisation Criteria for Energy Systems Analyses of Renewable Energy Integration. - Energy, Vol. 4, 2009, pp. 1236-1245.10.1016/j.energy.2009.05.004Search in Google Scholar

29 Peneva, V., I. Popchev, Fuzzy Multi-Criteria Decision Making Algorithms. - Compt. Rend. Acad. bulg. Sci., Vol. 63, 2010, pp. 979-992.Search in Google Scholar

30 Peneva, V., I. Popche v. Models for Decision Making by Fuzzy Relations and Fuzzy Numbers for Criteria Evaluations. - Compt. Rend. Acad. bulg. Sci., Vol. 62, 2009, pp. 1217-1222.Search in Google Scholar

31 Peneva, V., I. Popche v. Models for Fuzzy Multicriteria Decision Making Based on Fuzzy Relations. - Compt. Rend. Acad. bulg. Sci., Vol. 62, 2009, pp. 551-558.Search in Google Scholar

32 Peneva, V., I. Popche v. Multicriteria Decision Making Based on Fuzzy Relations. - Cybernetics and Information Technologies, Vol. 8, 2008, pp. 3-12.Search in Google Scholar

33 Peneva, V., I. Popche v. Multicriteria Decision Making by Fuzzy Relations and Weighting Functions for the Criteria. - Cybernetics and Information Technologies, Vol. 9, 2009, pp. 58-71.Search in Google Scholar

34 Perez, B., R. Minguez, R. Guanche. Offshore Wind Farm Layout Optimization Using Mathematical Programming Techniques. - Renew. Energ., Vol. 53, 2013, pp. 389-399.10.1016/j.renene.2012.12.007Search in Google Scholar

35 Saavedra-Moreno, B., S. Salcedo-Sanz, A. Paniagua-Tineo, L. Prieto, A. Portilla-Figueras. Seeding Evolutionary Algorithms with Heuristics for Optimal Wind Turbines Positioning in Wind Farms. - Renew. Energ., Vol. 36, 2011, pp. 2838-2844.10.1016/j.renene.2011.04.018Search in Google Scholar

36 Shakoor, R., M. Y. Hassan, A. Raheem, Y. K. Wu. Wake Effect Modeling: A Review of Wind Farm Layout Optimization Using Jensen’s Model. - Renew. Sust. Energ. Rev., Vol. 58, 2016, pp. 1048-1059.10.1016/j.rser.2015.12.229Search in Google Scholar

37 Smith, G., W. Schlez, A. Liddell, A. Neubert, A. Pena. Advanced Wake Model for Very Closely Spaced Turbines. - In: Proc. EWEC 2006, Athens. 2006.Search in Google Scholar

38 Sorkhabi, S. Y. D., D. A. Romero, G. K. Yan, M. D. Gu, J. Moran, M. Morgenroth, C. H. Amon. The Impact of Land Use Constraints in Multi-Objective Energy-Noise Wind Farm Layout Optimization. - Renew. Energ., Vol. 85, 2016, pp. 359-370.10.1016/j.renene.2015.06.026Search in Google Scholar

39 Tran, R., J. Wu, C. Denison, T. Ackling, M. Wagner, F. Neuman n. Fast and Effective Multi-Objective Optimisation of Wind Turbine Placement. - In: Proc. Genetic and Evolutionary Computation, 2013, pp. 1381-1388.10.1145/2463372.2463541Search in Google Scholar

40 Wan, C., J. Wang, G. Yang, X. Li, X. Zhang. Optimal Micro-Siting of Wind Turbines by Genetic Algorithms Based on Improved Wind and Turbine Models. - In: Proc. of 48th IEEE Conf. on Decision & Control and the 28th Chinese Control Conference, 2009.10.1109/CDC.2009.5399571Search in Google Scholar

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Language:
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Computer Sciences, Information Technology