Dynamic time-linkage evolutionary optimization: Definitions and potential solutions

Trung Thanh NGUYEN*, Xin YAO

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

8 Citations (Scopus)


Dynamic time-linkage optimization problems (DTPs) are special dynamic optimization problems (DOPs) where the current solutions chosen by the solver can influence how the problems might change in the future. Although DTPs are very common in real-world applications (e.g. online scheduling, online vehicle routing, and online optimal control problems), they have received very little attention from the evolutionary dynamic optimization (EDO) research community. Due to this lack of research there are still many characteristics that we do not fully know about DTPs. For example, how should we define and classify DTPs in detail; are there any characteristics of DTPs that we do not know; with these characteristics are DTPs still solvable; and what is the appropriate strategy to solve them. In this chapter these issues will be partially addressed. First, we will propose a detailed definition framework to help characterising DOPs and DTPs. Second, we will identify a new and challenging class of DTPs where it might not be possible to solve the problems using traditional methods. Third, an approach to solve this class of problems under certain circumstances will be suggested and experiments to verify the hypothesis will be carried out. Two test problems will be proposed to simulate the property of this new class of DTPs, and discussions of real-world applications will be introduced. © Springer-Verlag Berlin Heidelberg 2013.
Original languageEnglish
Title of host publicationMetaheuristics for Dynamic Optimization
EditorsEnrique ALBA, Amir NAKIB, Patrick SIARRY
Number of pages25
ISBN (Electronic)9783642306655
ISBN (Print)9783642306648, 9783642443701
Publication statusPublished - 2013
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503


Dive into the research topics of 'Dynamic time-linkage evolutionary optimization: Definitions and potential solutions'. Together they form a unique fingerprint.

Cite this