Many objective optimization and complex network analysis

Maulana, A. (2018)

Doctoral Thesis

This thesis seeks to combine two different research topics; Multi-Objective Optimization
and Complex Network Analysis.
Multi-Objective Optimization aims at finding a set of optimal, non-dominated
solutions for optimization problems with multiple (actually, many) conflicting objectives.
There is a wide range of applications of multi-objective optimization such as in
science, engineering design, network analysis, chemical processes, delivery of products,
economics and logistics, medical health and so forth. Since one often faces problems
with a larger number of objective functions to be optimized simultaneously, the research
topic has shifted to Many-Objective Optimization, which means optimization with (far)
more than three objective functions.
Complex network analysis is a research field that deals with analyzing large
networks. In this research line, there are some active research topics, such as
controlling complex networks, finding communities in a network, and measuring the
importance of nodes in networks. Due to the bigger amount of data and more difficult
problems arising in complex network analysis, research in this field has increased significantly. To this end, more complex networks has given the challenge of finding
better approaches in dealing with the problem to yield some adequate result of an analysis.

• Many-Objective Optimization
• Complex-Network Analysis
• Network Centrality
• Community Detection
• Network Immunization

• All authors: Maulana, A.
• Supervisor: Bäck, T.H.W.; Emmerich, M.T.M.
• Committee: Plaat, A.; Takes, F.; Verbeek, F.; Garlaschelli, D.; Ruchjana, B.; Liu, J.
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden Institute of Advanced Computer Science (LIACS), Faculty of Science, Leiden University
• Date: 2018-12-05
• ISBN (print): 9789463752275
• Sponsorship: Indonesian Endowment Fund for Education (LPDP)