Decision Making and Optimization in Changeable Spaces, A Paradigm Shift

• Main Authors: Larbani, Moussa, Yu, Po-Lung
• Format: Conference or Workshop Item
• Language: English
• Published: 2012
• Subjects: HB131 Methodology.Mathematical economics. Quantitative methods
• Online Access: http://irep.iium.edu.my/26758/1/Kuantan_Conference_2.ppt; http://irep.iium.edu.my/26758/

This paper proposes a new decision making/optimization paradigm, the decision making/optimization in changeable spaces (DM/OCS). The unique feature of DM/OCS is that it incorporates human psychology and its dynamics as part of the decision making process and allows the restructuring of the decision parameters. DM/OCS is based on Habitual Domain theory, the decision parameters, the concept of competence set, and the mental operators 7-8-9 principles of deep knowledge. The covering and discovering processes are formulated as DM/OCS problems. Some illustrative examples of challenging problems that cannot be solved by traditional decision making/optimization techniques are formulated as DM/OCS problems and solved. In addition, some directions of research related to innovation dynamics, management, artificial intelligence, artificial and e-economics, scientific discovery, and knowledge extraction are provided in the conclusion.