An Efficient Soft Set-Based Approach for Conflict Analysis

• Published in: PloS one Vol. 11; no. 2; p. e0148837
• Main Authors: Sutoyo, Edi, Mungad, Mungad, Hamid, Suraya, Herawan, Tutut
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.02.2016; Public Library of Science (PLoS)
• Subjects: Algorithms; Analysis; Applied mathematics; Biology and Life Sciences; Computation; Computer and Information Sciences; Computer applications; Conflict management; Decision making; Decision theory; Economic analysis; Information systems; Mathematical models; Medical diagnosis; Methods; Military operations; Models, Theoretical; Negotiations; Optimization techniques; People and Places; Physical Sciences; Politics; Set theory; Social Sciences; Malaysia; Kuala Lumpur Malaysia
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0148837

Conflict analysis has been used as an important tool in economic, business, governmental and political dispute, games, management negotiations, military operations and etc. There are many mathematical formal models have been proposed to handle conflict situations and one of the most popular is rough set theory. With the ability to handle vagueness from the conflict data set, rough set theory has been successfully used. However, computational time is still an issue when determining the certainty, coverage, and strength of conflict situations. In this paper, we present an alternative approach to handle conflict situations, based on some ideas using soft set theory. The novelty of the proposed approach is that, unlike in rough set theory that uses decision rules, it is based on the concept of co-occurrence of parameters in soft set theory. We illustrate the proposed approach by means of a tutorial example of voting analysis in conflict situations. Furthermore, we elaborate the proposed approach on real world dataset of political conflict in Indonesian Parliament. We show that, the proposed approach achieves lower computational time as compared to rough set theory of up to 3.9%.