Skip to main content
Erschienen in: Fuzzy Optimization and Decision Making 3/2018

22.12.2017

Interval fuzzy preferences in the graph model for conflict resolution

verfasst von: M. Abul Bashar, Keith W. Hipel, D. Marc Kilgour, Amer Obeidi

Erschienen in: Fuzzy Optimization and Decision Making | Ausgabe 3/2018

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

A new analysis technique, appropriate to situations of high preference uncertainty, is added to the graph model for conflict resolution methodology. Interval fuzzy stabilities are now formulated, based on decision makers’ (DMs’) interval fuzzy preferences over feasible scenarios or states in a conflict. Interval fuzzy stability notions enhance the applicability of the graph model, and generalize its crisp and fuzzy preference-based stability ideas. A graph model is both a formal representation and an analysis procedure for multiple participant-multiple objective decisions that employs stability concepts representing various forms of human behavior under conflict. Defined based on a type-2 fuzzy logic, an interval fuzzy preference for one state over another is represented by a subinterval of [0, 1] indicating an interval-valued preference degree for the first state over the second. The interval fuzzy stabilities put forward in this research are interval fuzzy Nash stability, interval fuzzy general metarational stability, interval fuzzy symmetric metarational stability, and interval fuzzy sequential stability. A state is interval fuzzy stable for a DM if moving to any other state is not adequately desirable to the DM; where adequacy is measured by the interval fuzzy satisficing threshold of the DM and farsightedness, involving possible moves and countermoves by DMs, is determined by the interval fuzzy stability notion selected. Note that infinitely many degrees in an interval-valued preference are preserved in characterizing the desirability of a move. A state from which no DM can move to any sufficiently desirable scenario is an interval fuzzy equilibrium, and is interpreted as a possible resolution of the strategic conflict under study. The new stability concept is illustrated through its application to an environmental conflict that took place in Elmira, Ontario, Canada. Insightful results are identified and discussed.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Al-Mutairi, M. S., Hipel, K. W., & Kamel, M. S. (2008). Fuzzy preferences in conflicts. Journal of Systems Science and Systems Engineering, 17, 257–276.CrossRef Al-Mutairi, M. S., Hipel, K. W., & Kamel, M. S. (2008). Fuzzy preferences in conflicts. Journal of Systems Science and Systems Engineering, 17, 257–276.CrossRef
Zurück zum Zitat Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2011). Fuzzy preferences in the sustainable development conflict. In Proceedings of the 2011 IEEE international conference on systems, man, and cybernetics, 2011 (pp. 3483–3488). Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2011). Fuzzy preferences in the sustainable development conflict. In Proceedings of the 2011 IEEE international conference on systems, man, and cybernetics, 2011 (pp. 3483–3488).
Zurück zum Zitat Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2012). Fuzzy preferences in the graph model for conflict resolution. IEEE Transactions on Fuzzy Systems, 20(4), 760–770.CrossRef Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2012). Fuzzy preferences in the graph model for conflict resolution. IEEE Transactions on Fuzzy Systems, 20(4), 760–770.CrossRef
Zurück zum Zitat Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2014). Fuzzy option prioritization for the graph model for conflict resolution. Fuzzy Sets and Systems, 246, 34–48.MathSciNetCrossRefMATH Bashar, M. A., Kilgour, D. M., & Hipel, K. W. (2014). Fuzzy option prioritization for the graph model for conflict resolution. Fuzzy Sets and Systems, 246, 34–48.MathSciNetCrossRefMATH
Zurück zum Zitat Bashar, M. A., Obeidi, A., Kilgour, D. M., & Hipel, K. W. (2016). Modeling fuzzy and interval fuzzy preferences within a graph model framework. IEEE Transactions on Fuzzy Systems, 24(4), 765–778.CrossRef Bashar, M. A., Obeidi, A., Kilgour, D. M., & Hipel, K. W. (2016). Modeling fuzzy and interval fuzzy preferences within a graph model framework. IEEE Transactions on Fuzzy Systems, 24(4), 765–778.CrossRef
Zurück zum Zitat Fang, L., Hipel, K. W., & Kilgour, D. M. (1993). Interactive decision making: The graph model for conflict resolution. New York: Wiley. Fang, L., Hipel, K. W., & Kilgour, D. M. (1993). Interactive decision making: The graph model for conflict resolution. New York: Wiley.
Zurück zum Zitat Fraser, N. M., & Hipel, K. W. (1984). Conflict analysis: Models and resolutions. New York: North-Holland.MATH Fraser, N. M., & Hipel, K. W. (1984). Conflict analysis: Models and resolutions. New York: North-Holland.MATH
Zurück zum Zitat Gao, J. (2013). Uncertain bimatrix game with applications. Fuzzy Optimization and Decision Making, 12(1), 65–78.MathSciNetCrossRef Gao, J. (2013). Uncertain bimatrix game with applications. Fuzzy Optimization and Decision Making, 12(1), 65–78.MathSciNetCrossRef
Zurück zum Zitat Hipel, K. W. (2009). Conflict resolution: Theme overview paper in conflict resolution. In K. W. Hipel (Eds.). Encyclopedia of Life Support Systems (EOLSS) (Vol. I, pp. 1–31). Oxford: EOLSS Publishers. http://www.eolss.net. Hipel, K. W. (2009). Conflict resolution: Theme overview paper in conflict resolution. In K. W. Hipel (Eds.). Encyclopedia of Life Support Systems (EOLSS) (Vol. I, pp. 1–31). Oxford: EOLSS Publishers. http://​www.​eolss.​net.
Zurück zum Zitat Hipel, K. W., Fang, L., Kilgour, D. M., & Haight, M. (1993). Environmental conflict resolution using the graph model. In Proceedings of the 1993 IEEE international conference on systems, man, and cybernetics, 1993 (pp. 153–158). Hipel, K. W., Fang, L., Kilgour, D. M., & Haight, M. (1993). Environmental conflict resolution using the graph model. In Proceedings of the 1993 IEEE international conference on systems, man, and cybernetics, 1993 (pp. 153–158).
Zurück zum Zitat Hipel, K. W., Fang, L., & Kilgour, D. M. (2008). Decision support systems in water resources and environmental management. Journal of Hydrologic Engineering, 13(9), 761–770.CrossRef Hipel, K. W., Fang, L., & Kilgour, D. M. (2008). Decision support systems in water resources and environmental management. Journal of Hydrologic Engineering, 13(9), 761–770.CrossRef
Zurück zum Zitat Hipel, K. W., & Obeidi, A. (2005). Trade versus the environment: Strategic settlement from a systems engineering perspective. Systems Engineering, 8(3), 211–233.CrossRef Hipel, K. W., & Obeidi, A. (2005). Trade versus the environment: Strategic settlement from a systems engineering perspective. Systems Engineering, 8(3), 211–233.CrossRef
Zurück zum Zitat Howard, N. (1971). Paradoxes of rationality: Theory of metagames and political behavior. Cambridge, MA: MIT Press. Howard, N. (1971). Paradoxes of rationality: Theory of metagames and political behavior. Cambridge, MA: MIT Press.
Zurück zum Zitat Howard, N. (1999). Confrontation analysis: How to win operations other than war. The Pentagon, Washington, DC: DoD C4ISR Cooperative Research Program. Howard, N. (1999). Confrontation analysis: How to win operations other than war. The Pentagon, Washington, DC: DoD C4ISR Cooperative Research Program.
Zurück zum Zitat Kilgour, D. M., & Eden, C. (Eds.). (2010). Handbook of group decision and negotiation. New York: Springer.MATH Kilgour, D. M., & Eden, C. (Eds.). (2010). Handbook of group decision and negotiation. New York: Springer.MATH
Zurück zum Zitat Kilgour, D. M., & Hipel, K. W. (2005). The graph model for conflict resolution: Past, present, and future. Group Decision and Negotiation, 14(6), 441–460.CrossRef Kilgour, D. M., & Hipel, K. W. (2005). The graph model for conflict resolution: Past, present, and future. Group Decision and Negotiation, 14(6), 441–460.CrossRef
Zurück zum Zitat Kuang, H., Bashar, M. A., Hipel, K. W., & Kilgour, D. M. (2015). Grey-based preference in a graph model for conflict resolution with multiple decision makers. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(9), 1254–1267.CrossRef Kuang, H., Bashar, M. A., Hipel, K. W., & Kilgour, D. M. (2015). Grey-based preference in a graph model for conflict resolution with multiple decision makers. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(9), 1254–1267.CrossRef
Zurück zum Zitat Li, K. W., Hipel, K. W., Kilgour, D. M., & Fang, L. (2004). Preference uncertainty in the graph model for conflict resolution. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 34(4), 507–520.CrossRef Li, K. W., Hipel, K. W., Kilgour, D. M., & Fang, L. (2004). Preference uncertainty in the graph model for conflict resolution. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 34(4), 507–520.CrossRef
Zurück zum Zitat Nurmi, H. (1981). Approaches to collective decision making with fuzzy preference relations. Fuzzy Sets and Systems, 6, 249–259.MathSciNetCrossRefMATH Nurmi, H. (1981). Approaches to collective decision making with fuzzy preference relations. Fuzzy Sets and Systems, 6, 249–259.MathSciNetCrossRefMATH
Zurück zum Zitat Rego, L. C., & dos Santos, A. M. (2015). Probabilistic preferences in the graph model for conflict resolution. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(4), 595–608.CrossRef Rego, L. C., & dos Santos, A. M. (2015). Probabilistic preferences in the graph model for conflict resolution. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45(4), 595–608.CrossRef
Zurück zum Zitat von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton: Princeton University Press.MATH von Neumann, J., & Morgenstern, O. (1944). Theory of games and economic behavior. Princeton: Princeton University Press.MATH
Zurück zum Zitat Xu, Z. S. (2004). On compatibility of interval fuzzy preference relations. Fuzzy Optimization and Decision Making, 3, 217–225.MathSciNetCrossRefMATH Xu, Z. S. (2004). On compatibility of interval fuzzy preference relations. Fuzzy Optimization and Decision Making, 3, 217–225.MathSciNetCrossRefMATH
Metadaten
Titel
Interval fuzzy preferences in the graph model for conflict resolution
verfasst von
M. Abul Bashar
Keith W. Hipel
D. Marc Kilgour
Amer Obeidi
Publikationsdatum
22.12.2017
Verlag
Springer US
Erschienen in
Fuzzy Optimization and Decision Making / Ausgabe 3/2018
Print ISSN: 1568-4539
Elektronische ISSN: 1573-2908
DOI
https://doi.org/10.1007/s10700-017-9279-7

Weitere Artikel der Ausgabe 3/2018

Fuzzy Optimization and Decision Making 3/2018 Zur Ausgabe

Premium Partner