Reference number : GC-2017-Q1-01941, amendment number : , agreement type : G, recipient legal name : Fang, Liping (Ryerson University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Environmental management problems often involve multiple stakeholders who usually have different objectives and value systems. The proposed research program aims to develop multiple participant decision making techniques for creatively addressing challenging environmental management problems. More specifically, the graph model for conflict resolution (GMCR) methodology will be significantly expanded and computerized systems will be designed and developed to support and operationalize newly devised methods. GMCR, originally developed by the applicant and his co-workers, constitutes a unique methodology for formally modeling and analyzing real-world multiple participant-multiple objective decision making problems. A decision support system called GMCR II, which allows GMCR to be applied to real-world conflicts, has been developed and used to systematically investigate disputes arising in many different fields. Within the proposed research program, further advancement of GMCR will be carried out in the following three areas. First, a new generation of a decision support system for conflict resolution along with implementation algorithms will be designed and developed based on recent new developments. Second, techniques for analytically solving the inverse analysis problem in GMCR will be devised using methods and results in matrix algebra. Third, an agent-based framework for modeling and simulating competitive and cooperative behavior under conflict will be significantly expanded to study conditions for the emergence of cooperation intended to effectively address common-pool resource management problems. Practical decision problems in environmental management and other areas will be utilized as case studies to develop, test, and improve the decision methods investigated. The methodologies and tools developed in the proposed research can be utilized by decision makers, practitioners, and researchers interested in sustainable environmental management, which is currently a significant challenge for the Canadian society. Graduate students will gain extensive knowledge and research training in developing multiple participant decision techniques, designing and implementing decision support systems, applying the new and improved techniques to complex environmental management problems, and disseminating results. The training received will prepare graduate students to pursue their careers in academia, research and development, government, and consulting. Results from the proposed research should significantly contribute to the theory and practice of multiple participant decision making techniques., program purpose french : Environmental management problems often involve multiple stakeholders who usually have different objectives and value systems. The proposed research program aims to develop multiple participant decision making techniques for creatively addressing challenging environmental management problems. More specifically, the graph model for conflict resolution (GMCR) methodology will be significantly expanded and computerized systems will be designed and developed to support and operationalize newly devised methods. GMCR, originally developed by the applicant and his co-workers, constitutes a unique methodology for formally modeling and analyzing real-world multiple participant-multiple objective decision making problems. A decision support system called GMCR II, which allows GMCR to be applied to real-world conflicts, has been developed and used to systematically investigate disputes arising in many different fields. Within the proposed research program, further advancement of GMCR will be carried out in the following three areas. First, a new generation of a decision support system for conflict resolution along with implementation algorithms will be designed and developed based on recent new developments. Second, techniques for analytically solving the inverse analysis problem in GMCR will be devised using methods and results in matrix algebra. Third, an agent-based framework for modeling and simulating competitive and cooperative behavior under conflict will be significantly expanded to study conditions for the emergence of cooperation intended to effectively address common-pool resource management problems. Practical decision problems in environmental management and other areas will be utilized as case studies to develop, test, and improve the decision methods investigated. The methodologies and tools developed in the proposed research can be utilized by decision makers, practitioners, and researchers interested in sustainable environmental management, which is currently a significant challenge for the Canadian society. Graduate students will gain extensive knowledge and research training in developing multiple participant decision techniques, designing and implementing decision support systems, applying the new and improved techniques to complex environmental management problems, and disseminating results. The training received will prepare graduate students to pursue their careers in academia, research and development, government, and consulting. Results from the proposed research should significantly contribute to the theory and practice of multiple participant decision making techniques., agreement title english : Multiple Participant Decision Approaches with Applications to Environmental Management, agreement title french : Multiple Participant Decision Approaches with Applications to Environmental Management, agreement number : RGPIN, agreement value : 170000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada