الفهرس 
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Abstract
Most of the existing mathematical tools for formal modeling,
reasoning and computing are crisp, deterministic and precise in
character. But, in real life situation, the problems in economics, engineering, environment, social science, physics, computer
sciences, medical science and many other diverse fields do not always involve crisp data. For this reason, we cannot successfully
use the traditional classical methods because of various types of
uncertainties presented in these problems. To exceed these uncertainties, some kinds of theories were given like theory of fuzzy sets
[Zadeh (1965)], rough sets [Pawlak (1982)], intuitionistic fuzzy sets
[Atanassov (1986)], i.e., which we can use as mathematical tools for
dealing with uncertainties. Moreover, Zadeh (2005) outlined the
generalized theory of uncertainty in a much broader perspective.
But all these theories have their inherent difficulties as what were
pointed out by Molodtsov (1999). He initiated the concept of soft
set theory as a new mathematical tool for dealing with vagueness
and uncertainties which is free from the above difficulties. Also, he
successfully applied the soft set theory into several directions, such
as topology [Molodtsov (2001), C. aˇgman et al. (2011), Min (2011),
Shabir and Naz (2011), Ayg¨unoˇglu and Ayg¨un (2012), Zorlutuna
et al. (2012), Hai-Long et al. (2015), Dizmana et al. (2016),
Tripathy and Acharjee (2017), Terepeta (2017)], various algebraic
structures [ Aktas and C. aˇgman (2007), Feng et al. (2008), Jun and
Park (2008), Vimala et al. (2017), Nazmul (2017) ], operations research [ Maji et al. (2003), Chen et al. (2005), Jiang et al. (2010)]
and especially decision-making [ Maji et al. (2002), C. aˇgman and
Enginoˇglu (2010), Feng et al. (2010 and 2012)