Donostia - San Sebastian, Spain, June 5-8, 2017
Service-oriented computing is becoming more and more prominent in the Internet environment with the rapid growth of Web services available on the internet. This raises issues for Web service providers such as Web service composition and location allocation, resource allocation and scheduling, etc. Furthermore, there are a number of potentially conflicting objectives (called Quality-of-Service, QoS) to be considered simultaneously in the problem such as response time, cost, reliability, safety, etc. In the era of cloud computing and Big Data, the number and complexity of Web services on the Internet is increasing rapidly. Traditional service composition approaches have come to a performance bottleneck.
Evolutionary computation has been successfully applied to many challenging real- world problems. This special session aims to solve the service-oriented computing problems with evolutionary computation techniques, covering all different evolutionary computation paradigms such as Genetic Algorithms (GAs), Genetic Programming (GP), Evolutionary Programming (EP), Evolution Strategies (ES), Memetic Algorithms (MAs), Learning Classifier Systems (LCS), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Differential Evolution (DE), and Evolutionary Multi- objective Optimization (EMO).
The scope of this special session includes both new theories and methods on how to solve the challenging service-oriented computing problems such as Web service composition and location allocation more effectively and efficiently. Authors are invited to submit their original and unpublished work to this special session.
The aim is to investigate in both the new theories and methods on how transfer learning can be achieved with different evolutionary computation paradigms, and how transfer learning can be adopted in evolutionary computation, and the applications of evolutionary computation and transfer learning in real-world problems. Authors are invited to submit their original and unpublished work to this special session.
Topics of interest include but are not limited to:
Hui Ma School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand. Hui.Ma@ecs.vuw.ac.nz Phone: +64-4-463 5657; Fax: +64-4-463 5045.
Yi Mei School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand. Yi.Mei@ecs.vuw.ac.nz Phone: +64-4-463 5233+8016; Fax: +64-4-463 5045.
Mengjie Zhang School of Engineering and Computer Science, Victoria University of Wellington, PO Box 600, Wellington, New Zealand. Mengjie.Zhang@ecs.vuw.ac.nz Phone: +64-4-463 5654; Fax: +64-4-463 5045
Dr. Hui Ma is a Senior Lecturer in computer science at Victoria University of Wellington, New Zealand.
Hui has more than 60 publications, including the top journals and conferences in databases, service computing, evolutionary computation, and conceptual modelling, such as Data & Knowledge Engineering (DKE), The International Conference on Conceptual Modeling (ER), and Genetic and Evolutionary Computation Conference (GECCO), International Conference on Database and Expert Systems Applications (DEXA). Hui is serving as the committee member of IEEE ECTC Task Force on Evolutionary Scheduling and Combinatorial Optimisation, and IEEE CIS Emergent Technology Technical Committee (ETTC). She is a guest editor of the special issue on Database- and Expert-Systems Applications on of LNCS Transactions on Large- Scale Data- and Knowledge-Centered Systems, and co-chair of a number of international conferences such as DEXA 2016, APCCM2017, ER 2017, APCCM2018, DEXA 2018. She is serving as a reviewer of over 20 international journals including the top journals in service computing and databases, and PC member of more than 50 international conferences.
Dr Yi Mei (S'09-M'13) is a Lecturer at the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. His research interests include evolutionary computation in scheduling, routing and combinatorial optimisation, as well as evolutionary machine learning, genetic programming, feature selection and dimensional reduction.
Yi has almost 40 publications, including the top journals in EC and Operations Research (OR) such as IEEE TEVC, IEEE Transactions on Cybernetics, European Journal of Operational Research, ACM Transactions on Mathematical Software, and top EC conferences (GECCO). As the sole investigator, he won the 2nd prize of the Competition at IEEE WCCI 2014: Optimisation of Problems with Multiple Interdependent Components. He received the 2010 Chinese Academy of Sciences Dean's Award (top 200 postgraduates all over China) and the 2009 IEEE Computational Intelligence Society (CIS) Postgraduate Summer Research Grant (three to four recipients all over the world). Yi is serving as the committee member of IEEE ECTC Task Force on Evolutionary Scheduling and Combinatorial Optimisation, IEEE CIS Task Force on EC for Feature Selection and Construction and IEEE CIS Task Force on Large Scale Global Optimisation. He is a guest editor of the Genetic Programming Evolvable Machine journal, and co-chair of a number of special sessions in international conferences such as IEEE CEC. He is serving as a reviewer of over 20 international journals including the top journals in EC and OR and PC member of almost 20 international conferences.
Dr Mengjie Zhang is currently Professor of Computer Science at Victoria University of Wellington, where he heads the interdisciplinary Evolutionary Computation Research Group. He is a member of the University Academic Board, a member of the University Postgraduate Scholarships Committee, a member of the Faculty of Graduate Research Board at the University, Associate Dean (Research and Innovation) in the Faculty of Engineering, and Chair of the Research Committee of the Faculty of Engineering and School of Engineering and Computer Science.
His research is mainly focused on evolutionary computation, particularly genetic programming, particle swarm optimisation and learning classifier systems with application areas of feature selection/construction and dimensionality reduction, computer vision and image processing, job shop scheduling, multi-objective optimisation, and classification with unbalanced and missing data. He is also interested in data mining, machine learning, and web information extraction. Prof Zhang has published over 400 research papers in refereed international journals and conferences in these areas. He has been serving as an associated editor or editorial board member for seven international journals including IEEE Transactions on Evolutionary Computation, the Evolutionary Computation Journal (MIT Press), IEEE Transactions on Emergent Technologies in Computational Intelligence, Genetic Programming and Evolvable Machines (Springer), Applied Soft Computing, IEEE Transactions on Emergent Topics in Computational Intelligence, Natural Computing, and Engineering Applications of Artificial Intelligence, and as a reviewer of over 30 international journals. He has been involving major EC conferences such as GECCO, IEEE CEC, EvoStar, IEEE SSCI and SEAL as a Chair. He has also been serving as a steering committee member and a program committee member for over 100 international conferences including all major conferences in evolutionary computation. Since 2007, he has been listed as one of the top ten world genetic programming researchers by the GP bibliography (http://www.cs.bham.ac.uk/~wbl/biblio/gp-html/index.html).
Prof Zhang is the Chair of the IEEE Emergent Technologies Technical Committee, the immediate Past Chair of the IEEE CIS Evolutionary Computation Technical Committee, a vice-chair of the IEEE CIS Task Force on Evolutionary Feature Selection and Construction, a vice-chair of the IEEE CIS Task Force on Evolutionary Computer Vision and Image Processing, and the founding chair of the IEEE Computational Intelligence Chapter in New Zealand.