SDMGRS: Soft Dominance Based Multi Granulation Rough Sets and Their Applications in Conflict Analysis Problems | Zendy

Noor Rehman | Zendy; Abbas Ali | Zendy; Muhammad Irfan Ali | Zendy; Choonkil Park | Zendy

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SDMGRS: Soft Dominance Based Multi Granulation Rough Sets and Their Applications in Conflict Analysis Problems

Author(s) -

Noor Rehman,

Abbas Ali,

Muhammad Irfan Ali,

Choonkil Park

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2841876

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

The classical rough set theory was presented by Pawlak, which is mainly concerned with the approximation of sets described by a single binary relation on the universe. In this paper, we initiate a multi attribute group decision making problems in the presence of multi attribute and multi decision in decision making with preferences. Then resolving the problem, using two different approximation strategies, i.e., seeking common reserving difference and seeking common rejecting difference, four kinds of soft dominance-based multi-granulation rough sets are presented, namely, soft dominance based optimistic multi-granulation rough sets and soft dominance based pessimistic multi-granulation rough sets and their applications in solving a multi agent conflict analysis decision problem. The proposed method addresses the limitations of the Pawlak model and Sun's conflict analysis model and thus improve these models. Finally, the results on labor management negotiation problems show that the proposed algorithms are more effective and efficient for feasible consensus strategy when compared with Sun's technique.

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