Canonical Duality Theory and Algorithms for Solving Some Challenging Problems in Global Optimization and Decision Science
Abstract
Supported by this grant, the PI and his group have successfully solved a series of challenging problems in computer science, global optimization and applied mathematics, including the well-known NP-hard max-cut problem and sensor location problem in network optimization. An open problem on triality theory left in 2003 has been solved. This theory can be used to identify both global and local extremal solutions and to design powerful algorithms for solving real-world problems. Within the past five years, 2 books, 5 journal special issues, and about 60 papers have been published. Four international conferences have been organized, including the 3rd World Congress of Global Optimization. A unified methodology and algorithm have been developed with real-world applications. This grant has been used to support and co-support three post-doctors, three PhD students, one part-time senior researcher, and more than 15 short-time visitors. The PI has been invited to delivery 18 plenary/keynote lectures at international conferences. The projects proposed in the proposal have been fully completed. The canonical duality theory is now considering as a breakthrough new methodological theory in multidisciplinary fields of applied mathematics, global optimization and nonlinear mechanics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 24, 2015
- Accession Number
- ADA628112
Entities
People
- David Y. Gao
Organizations
- Federation University Australia