Multi Criteria Decision Making Techniques for Asset Selection

: A majority of the problems faced by many sophisticated fields, such as, Medical, Engineering, Environment, Social, Financial Mathematics and Economics, are due to uncertainty and ambiguity. Decision-making methods play a crucial role in solving these problems by getting the optimal portfolio. The Fuzzy Soft Set (FSS) is one such decision-making method, which is easily solvable. In this article, an appropriate selection of assets is introduced in financial trading, with the help of different multi-criteria decision-making approaches, such as, Level Soft Set (LSS), Mean Potentiality Approach (MPA), Non-Fuzzy Set and Soft Hesitant Fuzzy Rough Set (SHFRS). Following comparison of the Performance Measure, it was found that the Soft Hesitant Fuzzy Rough Set was capable of constructing a portfolio of assets according to the investor’s preference. In addition to this assessment of the investment, the Firefly Optimization algorithm was used to obtain the proportion of assets in the portfolio. Furthermore, the Bombay Stock Exchange, India (BSE) data was used to check the effectiveness and performance of the Soft Hesitant Fuzzy Rough set algorithm, to note its effectiveness, based on the performance.

HIMPUNAN LEMBUT KABUR HESITANT DAN APLIKASINYA DALAM PENGAMBILAN KEPUTUSAN

Molodstov's soft set theory is a newly emerging mathematical tool to handleuncertainty. The soft set theory can be combined with other mathematical theory like asfuzzy set theory. This paper aims to extend hesitant fuzzy set to hesitant fuzzy soft sets.Then, the complement, "AND", "OR", union, intersection operations and De Morgan'slaw are dened on hesitant fuzzy soft sets. Finally, with the help of level soft set, thehesitant fuzzy soft sets are applied to a decision making problem.Kata Kunci: Soft set, Fuzzy set, Hesitant fuzzy set, Hesitant fuzzy soft set, Level softset

Hesitant Fuzzy Soft Set and Its Applications in Multicriteria Decision Making

Molodtsov’s soft set theory is a newly emerging mathematical tool to handle uncertainty. However, the classical soft sets are not appropriate to deal with imprecise and fuzzy parameters. This paper aims to extend the classical soft sets to hesitant fuzzy soft sets which are combined by the soft sets and hesitant fuzzy sets. Then, the complement, “AND”, “OR”, union and intersection operations are defined on hesitant fuzzy soft sets. The basic properties such as DeMorgan’s laws and the relevant laws of hesitant fuzzy soft sets are proved. Finally, with the help of level soft set, the hesitant fuzzy soft sets are applied to a decision making problem and the effectiveness is proved by a numerical example.