Portrait of Dr. Zhen LIU.

User Rating: 5 / 5

Star ActiveStar ActiveStar ActiveStar ActiveStar Active

The Institute of Applied Optimization welcomes Dr. Yan Chen [陈岩], who today has officially joined our team as researcher. Before joining our institute, he finished his PhD research at the Spatial Information Management and Modelling Department of the School of Spatial Planning of the TU Dortmund (Technische Universität Dortmund) in Germany. Dr. Chen is an expert in Geographic Information System (GIS), Remote Sensing, and Sponge City/Smart City applications as well as groundwater systems and hydrological simulations.

We are very happy that Dr. Chen joined our team. We are looking forward to working together on many interesting applications of GIS and computational intelligence.

User Rating: 3 / 5

Star ActiveStar ActiveStar ActiveStar InactiveStar Inactive

Our team warmly welcomes Mr. Lalin Heng, lecturer at the Department of Information Technology and Communication of the Institute of Technology of Cambodia (ITC) [វិទ្យាស្ថានបច្ចេកវិទ្យាកម្ពុជា] in Phnom Penh [ភ្នំពេញ], Cambodia [កម្ពុជា] for a research stay from February to March 2019. Mr. Heng has received his Master of Electrical Engineering with specialization in Information Technology in 2017 from the Gadjah Mada University, Yokyakarta, Indonesia and holds two Bachelor degrees, a Bachelor of Engineering in Computer Science also from ITC (2015) and a Bachelor of Education in TEFL from the Institute of Foreign Languages (IFL) of the Royal University of Phnom Penh (RUPP) [សាកលវិទ្យាល័យភូមិន្ទភ្នំពេញ], Phnom Penh, Cambodia (2018). He holds several professional certificates in computer networking both from Cisco and Huawei and has gathered work experience in several internships in this field, too. He has published four academic papers on routing and cell selection. The research interests of Mr. Heng include computer networks and security, which are important areas of application of optimization and computational intelligence. His work and interests are therefore closely related to the Distributed Computing research field of our institute. We are is looking forward to working with Mr. Heng. Welcome to Hefei University!

Portrait of Dr. Zhen LIU.
Star InactiveStar InactiveStar InactiveStar InactiveStar Inactive

Our team congratulates Xinlu Li [李新路], who, from today (2019-02-13) on, is Dr. Xinlu Li [李新路博士]! Earlier this year, Xinlu successfully defended his PhD thesis  "Energy-Efficient Swarm Intelligence based Routing Protocol for Wireless Sensor Networks" at the Technological University Dublin (TU Dublin) in Dublin, Ireland in front of Professor Liam Murphy from the University College Dublin (UCD) and Dr. Paul Doyle (TU Dublin). His work was co-supervised by Dr. Fred Mtenzi and Dr. Brian Keegan. Today his academic award has been approved by the Academic Council of TU Dublin. Congratulations, Dr. Li!

In the framework of his thesis, Dr. Li conducted research on Swarm Intelligence (SI) based routing for Wireless Sensor Networks (WSNs). SI is a meta-heuristic methodology used to solve numerical optimization problems by simulating swarm behaviors found in nature. These techniques demonstrate the desirable properties of interpretability, scalability, effectiveness, and robustness. There is a similarity between bio-inspired systems and routing in networks, especially in WSNs. Dr. Li designed a SI-based routing protocol capable of being deployed on large-scale WSNs to ensure efficient energy usage and prolonging the network lifetime.

Xinlu Li after his PhD defense.
Dr. Xinlu Li after his PhD defense. Left to right: Dr. Brian Keegan (supervisor), Dr. Xinlu Li, and the external examiners Prof. Liam Murphy (UDC) and Dr. Paul Doyle (TU Dublin).

User Rating: 5 / 5

Star ActiveStar ActiveStar ActiveStar ActiveStar Active

On Wednesday, 2019-01-30, we presented our paper "An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search," co-authored by Thomas Weise, Zijun Wu, and Markus Wagner at the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19).

Thomas Weise, Zijun Wu, and Markus Wagner. An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), January 27 – February 1, 2019, Honolulu, Hawaii, USA, pages 2395–2402. Palo Alto, CA, USA: AAAI Press. ISBN: 978-1-57735-809-1
doi:10.1609/aaai.v33i01.33012395 / pdf@IAO / pdf@AAAI / slides / poster

The conference was very nice and interesting. The seven sessions on "Search, Constraint Satisfaction and Optimization" as well as the ten sessions on "Game Theory and Economic Paradigms" showed that our research fields are core topics at one of the most important venues on soft computing. It was very nice presenting our work in such a context and we had several interesting discussions with interested researchers.

User Rating: 5 / 5

Star ActiveStar ActiveStar ActiveStar ActiveStar Active

The paper submission deadline of the 2019 IEEE Congress on Evolutionary Computation has been extended until January 31, 2019. As a result, we are happy to announce that there are also two more weeks for authors to submit their papers to our Special Session on Benchmarking of Evolutionary Algorithms for Discrete Optimization (BEADO).

Evolutionary Computation (EC) is a huge and expanding field, attracting more and more interests from both academia and industry. It includes a wide and ever-growing variety of optimization algorithms, which, in turn, are applied to an even wider and faster growing range of different problem domains, including discrete optimization. Benchmarking is the engine driving research in the fields of Evolutionary Algorithms (EAs) for decades, while its potential has not been fully explored. With our special session, we want to bring together experts on benchmarking, evolutionary computation algorithms, and discrete optimization and provide a platform for them to exchange findings, to explore new paradigms for performance comparison, and to discuss issues such as

  • modelling of algorithm behaviors and performance
  • visualizations of algorithm behaviors and performance
  • statistics for performance comparison (robust statistics, PCA, ANOVA, statistical tests, ROC, …)
  • evaluation of real-world goals such as algorithm robustness, and reliability
  • theoretical results for algorithm performance comparison
  • comparison of theoretical and empirical results
  • new benchmark problems
  • the comparison of algorithms in “non-traditional” scenarios such as
    • multi- or many-objective domains
    • parallel implementations, e.g., using GGPUs, MPI, CUDA, clusters, or running in clouds
    • large-scale problems or problems where objective function evaluations are costly
    • dynamic problems or where the objective functions involve randomized simulations or noise
  • comparative surveys with new ideas on
    • dos and don'ts, i.e., best and worst practices, for algorithm performance comparison
    • tools for experiment execution, result collection, and algorithm comparison
    • benchmark sets for certain problem domains and their mutual advantages and weaknesses

Please visit the special session website for more information. Here you can download the BEADO Special Session Call for Papers (CfP) in PDF format and here as plain text file.

feed-image rss feed-image atom