Special Session on Nature-inspired Computing in Intelligent Network Systems



Optimization and application of network environments have attracted enormous amount of concentration and brought huge impact on the research orientations, living form of human beings and growth of economy in the last decade. The development on the number of users of social media and network application, the colossal increase of mobile devices, and the vast volume of information hidden in distributed data centers yield the necessity of establishing effective mechanism or algorithms for solving optimization problems in network system, and the trends become much more apparent on several aspects in the last few years due to the COVID-19 pandemic, which causes the requirements of physical division and virtual connection. Fortunately, the emerging technologies of high-performance computing provide powerful tools for the development of algorithms for representing, optimizing, and reasoning network systems through computational intelligence methods.

Keywords: Nature-inspired Computing, Communication network systems, Transportation and logistics, Information network systems, Social network systems, Financial and economic network systems

Aim and Scope

This special session aims at promoting studies on the development of nature-inspired approaches, including evolutionary computation, swarm intelligence, metaheuristics, and artificial neural networks, for network-system representation, optimization, and reasoning. Topics of interest include but not limited to:

·        Communication network systems

The importance of communication and telecommunications have raised up since the drastically increased number of mobile devices, and different types of communication for different circumstances, such as mobile, satellite, optical, and voice communications, require to be optimized at certain levels or in terms of varying aspects, including switching, routing, and transmission systems, which may involve the design of station and antenna and the simulation of communication systems. In addition, many issues exist in the optimization of a communication network system, including information and speech processing, intrusion detection, error control coding, compression and cryptography, propagation and channel modelling, protocol design, etc.

·        Transportation and logistics network systems

The indispensability of optimization for transportation and logistics is extremely obvious in recent years, especially after the pandemic of COVID-19 and the Suez Canal obstruction. The optimization issues remaining to be solved include transportation and supply networks, logistics, supply chain management, freight and passenger services, tracking and tracing, fleet and order management, modelling and traffic management, traffic simulation, individual and public transportation, inventory optimization; routing and scheduling, etc.

·        Information network systems

The explosion on the growth of data and information gives prominence to the information network system and data mining. Issues in this topic cover data distribution and sharing, distributed data systems, inter-organizational communication, dynamic data network, heterogeneous data analysis, etc.

·        Social network systems

The increase of population and the widespread of individual and mobile devices enlarge the utility of social network and therefore facilitate the importance of optimization over it. The issues include action policies analysis, networking strategies search, network and friendship management, identification of interests, advertisement of interests, hierarchical networks distribution, distributed games, behavior analysis, inter-personal communication, group communication, etc.

·        Financial and economic network systems

The real lives of human beings have close connection to the finance and economy. For improving the benefit of the whole community of people, the optimization, detection, and forecasting for financial and economic network system are inevitable. The issues consist of system modelling, market prices forecasting, price tracking, invest strategies search, portfolio strategies search, etc.

·        General network problems

Some other issues are referred to as general network problems, including parallel and distributed systems, networks and graph problems, unconstrained and constrained network design problems, structural and computational complexity, adaptivity to environmental variations, robustness to network changes and failures, effectiveness and scalability of performance, location and link design, reliability and failure, corporate network design, location placement, network physical and software architecture, network hardware and software technologies, operations, maintenance, and management, signaling and control, active networks, network services and applications, etc.


This special session is organized by IEEE CIS ISATC Task Force on Intelligent Network Systems (TF-INS).

Rung-Tzuo Liaw
Assistant Professor, Fu Jen Catholic University, Taiwan, Email: rtliaw@csie.fju.edu.tw

Dr. Liaw obtained his bachelor degree of science from National Taiwan University in 2009 and the PhD degree from National Chung Cheng University in Taiwan in 2017. He is an honor member of Phi Tau Phi scholastic honor society since 2014. Dr. Liaw has published several journal and international conference papers. He is currently an assistant professor at Fu Jen Catholic University. His research interests include evolutionary computation, evolutionary multitask optimization, transfer learning, evolutionary learning and data mining, surrogate-based optimization, and multiobjective optimization. Dr. Liaw has entered the editorial board of Memetic Computing journal since 2020. He has served as the chair of Intelligence Network Systems task force in IEEE CIS since 2021.


Yu-Wei Wen
Assistant Professor, National United University, Taiwan, Email: ywwen@nuu.edu.tw

Dr. Wen received his B.S. degree and Ph.D. degree in computer science and information engineering from National Chung Cheng University, Taiwan, in 2015 and 2022, respectively. He is currently an assistant professor with the Department of Computer Science and Information Engineering, National United University, Taiwan. His research interests include evolutionary computation, memetic computing, evolutionary multitask optimization, machine learning, and algorithmic music composition.


Chuan-Kang Ting
Professor, National Tsing Hua University, Taiwan, Email: ckting@cs.nthu.edu.tw

Chuan-Kang Ting received the B.S. degree from National Chiao Tung University, the M.S. degree from National Tsing Hua University, and the Dr. rer. nat. degree in Computer Science from Paderborn University, Germany. He is currently a Professor of Department of Computer Science, National Tsing Hua University, Taiwan. His research interests include evolutionary computation, computational intelligence, artificial intelligence, machine learning, and their applications in intelligent systems, smart manufacturing, data mining, music and art. Dr. Ting is the Editor-in-Chief of IEEE Computational Intelligence Magazine and Memetic Computing journal, and an Associate Editor of IEEE Transactions on Evolutionary Computation. He served as the IEEE Computational Intelligence Society (CIS) Newsletter Editor, the IEEE CIS Webmaster, the Chair of IEEE CIS Chapters Committee, and the Chair of IEEE CIS Creative Intelligence Task Force. Dr. Ting has been involved in organization of many international conferences, symposiums, workshops, and special sessions. He was the Special Session Chair of IEEE WCCI 2016, WCCI 2018, and CEC 2019, the Chair of IEEE Symposium on Computational Intelligence for Creativity and Affective Computing 2013, the Program Chair of TAAI (2012, 2015, 2019), and the Organizing Chair of AI Forum (2012, 2023). He is the President of Taiwanese Association for Artificial Intelligence.