Table of Contents Author Guidelines Submit a Manuscript
Advances in Fuzzy Systems
Volume 2018, Article ID 4279236, 9 pages
Research Article

Optimization of Risk and Return Using Fuzzy Multiobjective Linear Programming

Department of Mathematics, Maulana Azad National Institute of Technology, Bhopal (MP), India

Correspondence should be addressed to Darsha Panwar; moc.liamg@ahsrad.rawnap

Received 11 May 2018; Revised 25 July 2018; Accepted 14 August 2018; Published 3 September 2018

Academic Editor: Zeki Ayag

Copyright © 2018 Darsha Panwar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Markowitz, “Portfolio selection,” The Journal of Finance, vol. 7, no. 1, pp. 77–91, 1952. View at Publisher · View at Google Scholar
  2. H. Konno and H. Yamazaki, “Mean-absolute deviation portfolio optimization model and its applications to Tokyo stock market,” Management Science, vol. 37, no. 5, pp. 519–531, 1991. View at Publisher · View at Google Scholar
  3. M. G. Speranza, “Linear programming models for portfolio optimization,” Finance, vol. 14, pp. 107–123, 1993. View at Google Scholar
  4. P. Gupta, M. K. Mehlawat, and A. Saxena, “A hybrid approach to asset allocation with simultaneous consideration of suitability and optimality,” Information Sciences, vol. 180, no. 11, pp. 2264–2285, 2010. View at Publisher · View at Google Scholar · View at Scopus
  5. G. Sekar, “Portfolio optimization using neuro fuzzy system in Indian stock market,” Journal of Global Research in Computer Science, vol. 3, no. 4, pp. 44–47, 2012. View at Google Scholar
  6. P. Gupta, M. K. Mehlawat, and A. Saxena, “Hybrid optimization models of portfolio selection involving financial and ethical considerations,” Knowledge-Based Systems, vol. 37, pp. 318–337, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. M. K. Mehlawat, “Behavioral optimization models for multicriteria portfolio selection,” Yugoslav Journal of Operations Research, vol. 23, no. 2, pp. 279–297, 2013. View at Publisher · View at Google Scholar · View at MathSciNet
  8. M. A. Sarokolaei, H. M. Salteh, and A. Edalat, “Presenting a Fuzzy Model for Fuzzy Portfolio Optimization with the Mean Absolute Deviation Risk Function,” European Online Journal of Natural and Social Science, vol. 2, no. 3, pp. 1793–1799, 2013. View at Google Scholar
  9. M. E. H. Sadati and A. Doniavi, “Optimization of fuzzy random portfolio selection by implementation of harmony search algorithm,” nternational Journal of Engineering Trends and Technology, vol. 8, no. 2, pp. 60–64, 2014. View at Google Scholar
  10. F. Konak and B. Bagc A, “Fuzzy Linear Programming on Portfolio Optimization: Empirical Evidence from FTSE 100 Index,” Global Journal of Management and Business Research, vol. 16, no. 2, pp. 57–61, 2016. View at Google Scholar
  11. Y. Wang, Y. Chen, and Y. Liu, “Modelling portfolio optimization problem by probability-credibility equilibrium risk criterion,” Mathematical Problems in Engineering, Article ID 9461021, 2016. View at Google Scholar
  12. A. Jagongo and V. S. Mutswenje, “A survey of the factors influencing investment decisions: the case of individual investors at the NSE,” International Journal of Humanities and Social Science, vol. 4, no. 4, pp. 92–102, 2014. View at Google Scholar
  13. T. L. Saaty, The Analytic Hierarchy Process, McGraw-Hill, New York, NY, USA, 1980. View at MathSciNet
  14. D. Pelleg and A. W. Moore, “X-means: Extending K-means with Efficient Estimation of the Number of Clusters,” in Proceedings of the In of the Seventeenth International Conference on Machine Learning, pp. 727–734, 2000.
  15. S. K. Bharati and S. R. Singh, “Solving multi objective linear programming problems using intuitionistic fuzzy optimization method: a comparative study,” nternational Journal of Modelling and Optimization, vol. 4, no. 1, pp. 10–16, 2014. View at Google Scholar