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We happily bid our welcome to Mr. Raphaël Cosson, who just started his Master's research project "Algorithm Selection for Discrete Black-Box Optimization Problems" under the supervision of Prof. Dr. Carola Doerr and co-supervision of Prof. Dr. Thomas Weise. Mr. Cosson will conduct his research at the Laboratoire d'informatique de Paris 6 (LIP6) of the Sorbonne University in Paris, France during Summer 2019. His work is at the intersection of algorithm configuration, algorithm benchmarking, and the theory of optimization. As basis for his research, he will use and extend the Iterative Optimization Heuristics Profiler (IOHprofiler), an awesome tool for benchmarking and evaluating optimization algorithms, in conjunction with the tunable benchmark model developed at our group. We are looking forward to an interesting and productive collaboration.

  • Carola Doerr, Hao Wang, Furong Ye, Sander van Rijn, and Thomas Bäck. IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristics. October 2018. arXiv e-prints:1810.05281.
    pdf / IOHprofiler / sources
  • Thomas Weise and Zijun Wu. Difficult Features of Combinatorial Optimization Problems and the Tunable W-Model Benchmark Problem for Simulating them. In Companion Material Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018), July 15-19 2018, Kyoto, Japan, pages 1769-1776, ISBN: 978-1-4503-5764-7. ACM.
    doi:10.1145/3205651.3208240 / pdf / slides / source codes
Portrait of Dr. Zhen LIU.

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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.

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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.

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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).

Abstract

Wireless Sensor Networks (WSNs) consist of a large number of distributed sensor nodes and have broad application prospects in many fields, including agriculture and industry. Due to the limitations of WSN sensor nodes power supplies, processing capacity and communication channel, the most important challenge of a routing protocol for WSNs is the energy consumption and the extension of the network lifetime. Dr. Li's thesis presents a design for a Swarm Intelligence (SI) based routing protocol capable of being deployed on large-scale WSNs to ensure efficient energy usage and prolonging the network lifetime. After an initial study of the characteristics of the Ant Colony Optimization (ACO) framework and hierarchical networks, an ACO-based clustering routing algorithm, ACCR, was proposed. ACCR presented a novel approach by providing a clustering algorithm to divide the network into several clusters along with an ACO based routing algorithm used in inter-cluster communication. The clustering algorithm is developed with an estimating average energy scheme. ACCR considers both the energy levels and path length as key metrics when updating the local heuristic value and pheromone trail. To enhance the performance of ACCR, an energy efficient load balancing ACO-based routing algorithm for WSNs (EBAR) is then presented. EBAR utilizes a pseudo-random proportional scheme in the routing discovery algorithm and an opportunistic broadcast algorithm instead of flooding for control packets. Furthermore, EBAR presents an improved metaheuristic update algorithm. Next, a novel hybrid SI-based routing algorithm, FSACO, is proposed. FSACO combines the Artificial Fish Swarm Algorithm (AFSA) with ACO with the result of reducing the convergence time and avoiding stagnation. FSACO was developed with an AFSA-based initial route discovery algorithm and a dynamic crowd factor combined with an ACO routing algorithm. FSACO demonstrated a 68.6% improvement in energy efficiency performance when compared current best practice WSN routing algorithm. Lastly, the performance evaluation of the aforementioned SI-based routing algorithms is verified by simulations and a physical testbed. The simulation and testbed results validate the improvements of the proposed methods in terms of better energy efficiency and longer network lifetime.

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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. Palo Alto, CA, USA: AAAI Press. accepted for publication

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.

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