Affiliations: [a] Department of Mathematics, Mersin University, Mersin, Turkey
| [b] Department of Mathematics, University of the Punjab, Lahore, Pakistan
| [c] Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa, Saudi Arabia
Correspondence:
[*]
Corresponding author. Ashraf Al-Quran, Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa 31982, Saudi Arabia. E-mail: [email protected].
Abstract: Introduction:The soft set theory has drawn the attention of many researchers, particularly for dealing with uncertainty in decision-making problems. Despite its remarkable advantages, the soft set theory has only been used to tackle decision-making problems that aim to choose the best option. However, there exist different forms of decision-making problems that involve different forms of uncertainty. Methods:In this study, we present various algorithms based on the soft set theory in order to handle the cases where one has different uncertainty forms in decision-making problems. Some new concepts such as object code, personal object code, parameter significance weight and new distance measures have been introduced to the literature for the construction of these algorithms. Furthermore, we show the application results of those algorithms and provide several examples. Results and Conclusions:As a result, a comparison among the application results of the algorithms implies that the best objects might not always yield the most efficient outcomes.
Keywords: Soft set, D-metric space, parametric distance, algorithm, decision making
