Multiple Participant Decision Approaches with Applications to Environmental Management

环境管理问题往往涉及多个利益相关者，他们通常具有不同的目标和价值体系。拟议的研究计划旨在开发多参与者决策技术，以创造性地解决具有挑战性的环境管理问题。更具体地说，将大大扩展解决冲突的图表模型(GMCR)方法，并将设计和开发计算机化系统，以支持和实施新制定的方法。GMCR最初是由申请人和他的同事开发的，它构成了一种独特的方法，用于形式化地建模和分析现实世界中的多参与者-多目标决策问题。开发了一个称为GMCR II的决策支持系统，它允许将GMCR应用于现实世界的冲突，并用于系统地调查许多不同领域产生的争端。在拟议的研究计划内，GMCR将在以下三个方面进一步推进。首先，将根据最近的新发展，设计和开发新一代冲突解决决策支持系统以及执行算法。其次，将使用矩阵代数中的方法和结果来设计解析地解决GMCR中的逆分析问题的技术。第三，一个基于智能体的框架，用于模拟和模拟冲突下的竞争和合作行为，将大大扩展到研究出现合作的条件，目的是有效地解决共同池资源管理问题。环境管理和其他领域的实际决策问题将作为案例研究，以开发、测试和改进所调查的决策方法。拟议研究中开发的方法和工具可供对可持续环境管理感兴趣的决策者、从业者和研究人员使用，可持续环境管理目前是加拿大社会面临的重大挑战。研究生将在开发多参与者决策技术、设计和实施决策支持系统、将新的和改进的技术应用于复杂的环境管理问题以及传播结果方面获得广泛的知识和研究培训。所接受的培训将为研究生在学术界、研发、政府和咨询等领域的职业生涯做好准备。建议的研究结果将对多参与者决策技术的理论和实践做出重大贡献。

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.