Canonical duality-triality theory: bridge between nonconvex analysis/mechanics and global optimization in complex system

David Yang Gao, Ning Ruan, Vittorio Latorre

Research output: Chapter in Book/Report/Conference proceedingChapter (Book)Otherpeer-review

Abstract

Canonical duality-triality is a breakthrough methodological theory, which can be used not only for modeling complex systems within a unified framework, but also for solving a wide class of challenging problems from real-world applications. This paper presents a brief review on this theory, its philosophical origin, physics foundation, and mathematical statements in both finite- and infinite-dimensional spaces. Particular emphasis is placed on its role for bridging the gap between nonconvex analysis/mechanics and global optimization . Special attentions are paid on unified understanding the fundamental difficulties in large deformation mechanics, bifurcation/chaos in nonlinear science, and the NP-hard problems in global optimization, as well as the theorems, methods, and algorithms for solving these challenging problems. Misunderstandings and confusion on some basic concepts, such as objectivity , nonlinearity, Lagrangian , and generalized convexities are discussed and classified. Breakthrough from recent challenges and conceptual mistakes by M. Voisei, C. Zălinescu and his coworker are addressed. The paper is ended with some open problems and future works in global optimization and nonconvex mechanics.
Original languageEnglish
Title of host publicationCanonical Duality Theory
Subtitle of host publicationUnified Methodology for Multidisciplinary Study
EditorsDavid Gao, Vittorio Latorre, Ning Ruan
Place of PublicationCham Switzerland
PublisherSpringer
Chapter1
Pages1-47
Number of pages47
Edition1st
ISBN (Electronic)9783319580173
ISBN (Print)9783319580166
DOIs
Publication statusPublished - 2017
Externally publishedYes

Publication series

NameAdvances in Mechanics and Mathematics
PublisherSpringer
Volume37
ISSN (Print)1571-8689
ISSN (Electronic)1876-9896

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