Our Institute warmly welcomes our distinguished guest Prof. Dr. Rolf H. Möhring from the Fachgebiet Kombinatorische Optimierung und Graphenalgorithmen (COGA) of the Institut für Mathematik at the Technische Universität Berlin (TUB) in Berlin, Germany. Prof. Möhring will stay with us for a short research visit from November 5 to 7, 2018. During his stay, he conducts joint research with our  team. This is his second visit this year, after his trip to our group trip in June, where he gave a very interesting research talk.

Today, 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, has been accepted at the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) to be held in January 27 to February 1, 2019 in Honolulu, Hawaii, USA.

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

Portrait of Dr. Zhen LIU.

The Institute of Applied Optimization welcomes Xinlu Li [李新路], who today has officially joined our team as researcher. He also currently is finishing his PhD in Computer Science under the supervision of Dr. Fred Mtenzi and Dr. Brian Keegan at the Technological University Dublin (TU Dublin, formerly named Dublin Institute of Technology, DIT) in Dublin, Ireland. He received his M.Sc. from Anhui University [安徽大学], Hefei, Anhui, China in 2009. His research is focused on energy efficient routing protocol design for large-scale Wireless Sensor Networks based on Swarm Intelligence Algorithms.

We are very happy to have Mr. Li in our team and look forward to working together on many interesting applications of optimization methods.

I am happy to announce that our group has moved into our new offices in the new building 52 with the nice name [合肥学院综合实验楼]. While the new offices are still temporary, they are very nice and modern. We not just have much more space than before, all the members of our young group can now also finally be co-located, which will make collaboration much easier. We are very thankful for the support of our university and faculty. The new building is quite beautiful, modern, and even equipped with solar panels on the facade! Our campus is now growing quickly and, with the generous support of the city and the government, our university adds more and more facilities and buildings.

Today, our application for a Special Issue on Benchmarking of Computational Intelligence Algorithms was accepted by the Applied Soft Computing journal published by Elsevier B.V. and indexed by SCIE and EI. Here you can download the Call for Papers (CfP) of the Special Issue in PDF format and here as plain text file.

Computational Intelligence (CI) is a huge and expanding field which is rapidly gaining importance, attracting more and more interests from both academia and industry. It includes a wide and ever-growing variety of optimization and machine learning algorithms, which, in turn, are applied to an even wider and faster growing range of different problem domains. For all of these domains and application scenarios, we want to pick the best algorithms. Actually, we want to do more, we want to improve upon the best algorithm. This requires a deep understanding of the problem at hand, the performance of the algorithms we have for that problem, the features that make instances of the problem hard for these algorithms, and the parameter settings for which the algorithms perform the best. Such knowledge can only be obtained empirically, by collecting data from experiments, by analyzing this data statistically, and by mining new information from it. Benchmarking is the engine driving research in the fields of optimization and machine learning for decades, while its potential has not been fully explored. Benchmarking the algorithms of Computational Intelligence is an application of Computational Intelligence itself! This special issue of the EI/SCIE-indexed Applied Soft Computing journal published by Elsevier B.V. solicits novel contributions from this domain.

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