EVOLVE International Conference

EVOLVE 2014 July 1-4
Beijing, China

EVOLVEMain

Program Committee

First Name Last Name Affiliation
Josiah Adeyemo  
Thomas Baeck  
Vitor Basto Fernandes  
Francisco Chicano  
Tudor Dan Mihoc  
Luis Gerardo De La Fraga  
Andre Deutz  
Jianguo Ding  
Dan Dumitrescu Babes-Bolyai University
Enrique Dunn  
Michael T.M. Emmerich Leiden University
Vitor Basto Fernandes Instituto Politecnico de Leiria
Francisco Fernandez  
Marc Eduard Frincu University of Southern California
Edgar Galvan  
Noemi Gasko  
Stephane Genaud ENSIIE Engineering School
David Iclanzan  
Adrian Iftene Faculty of Computer Science Iasi "Al.I.Cuza" University
Ahmed Kattan  
Joanna Kolodziej  
Pierrick Legrand IMB/INRIA/UBDX2
Rui Li  
Jing Liu  
Francisco Luna  
Rodica Lung Babes-Bolyai University
Asep Maulana LIACS
James McDermott  
Nicolas Monmarch?  
Sanaz Mostaghim  
Reka Nagy  
Gustavo Olague  
Eunice Ponce-De-Leon  
Eduardo Rodriguez-Tello  
Christoph Schommer  
Ignacio Segovia-Dominguez  
Ofer Shir  
Mihai Suciu  
Alexandru-Adrian Tantar Security and Trust (SNT), University of Luxembourg
Emilia Tantar University of Luxembourg
Leonardo Trujillo  
Sergio Ivvan Valdez  
Hao Wang LIACS, Leiden University
Fatos Xhafa  
Iryna Yevseyeva Newcastle University
Daniela Zaharie Mathematics and Computer Science, West University of Timisoara
Zhiwei Zhang  

Design choices and experience using real-world distributed systems

Aim:

This session is targeted to innovative solutions, applications, commercial systems and architectures for real-world distributed systems. Theoretical analyses as well as experimental studies are welcome.

 

Submission:

Authors are invited to submit through Easychair either

* full-length papers (maximum 15 pages) containing original results (to be published in Springer series "Studies in Computational Intelligence", as proceedings or post-proceedings)

or

* extended abstracts (maximum 4 pages) presenting work in progress or software prototypes (to be included in an electronic proceedings with ISBN).

All submissions must be in English and edited in Word, using the templates of the Springer book series

 

Topics:

Topics of interest include, but are not limited to:
·         Cloud Computing
·         Web and Mobile Apps back-end design
·         Integration of complex enterprise application
·         Real world cases using Service Oriented Architecture
·         Design of Software as a Service solutions
·         Software architectures and new computational approaches for Big Data
·         Knowledge and wisdom obtained from implementing solutions for distributed computing problems

 

Important Dates:

March 8
  2015   deadline for paper submission
March 22
  2015   author notification
April 5   2015   final camera-ready papers due
June 18-24   2015   EVOLVE 2015 conference dates

 

Program Committee:

Lenuța Alboaie   Alexandru Ioan Cuza University of Iasi, Romania
Alexandru Archip
  Gheorghe Asachi Technical University of Iasi, Romania
Silviu Bejinariu
  Gheorghe Asachi Technical University of Iasi, Romania
Mihaela Colhon    University of Craiova, Romania
Mihai Dimian   Stefan cel Mare University of Suceava, Romania and Howard University, Washington, USA
Corina Forăscu
  Alexandru Ioan Cuza University of Iasi, Romania
Adrian Iftene   Alexandru Ioan Cuza University of Iasi, Romania
Cornelius Croitoru   Alexandru Ioan Cuza University of Iasi, Romania
Vlad Posea   Politehnica University, Bucharest, Romania
Dana Simian   Lucian Blaga University of Sibiu, Romania
Sînică Alboaie   Axiologic SA, Romania
Florin Stoica   Lucian Blaga University of Sibiu
Horia-Nicolai Teodorescu   Institute of Computer Science of the Romanian Academy, Iasi branch and Gheorghe Asachi Technical University of Iasi, Romania
Mircea Vaida   Technical University of Cluj Napoca, Romania

 

Co-chairs:

Lenuța Alboaie    Alexandru Ioan Cuza University of Iasi, Romania
Corina Forăscu   Alexandru Ioan Cuza University of Iasi, Romania
Adrian Iftene   Alexandru Ioan Cuza University of Iasi, Romania

Evolving from Natural Computing and Data Mining

 Organizers: Mihaela Breaban, Alexandru Ioan Cuza University of Iasi, Romania
  Madalina Raschip, University of Neuchatel, Switzerland
  Dragos Gavrilut, Alexandru Ioan Cuza University of Iasi, Romania
In the spirit of the host conference, the workshop is intended as a bridge between Natural Computing and Data Mining, with the aim of promoting research that spans across the two fields.
The most commonly encountered tasks from data mining, such as feature selection, clustering, classification, association rules mining, model building, etc. can be translated into optimization tasks. Evolutionary computation techniques work as general optimizers with proven efficiency in solving optimization problems, so it is a natural consequence to approach data mining task by using evolutionary computation.
On the other hand, learning from the past experience of an algorithm can improve the performance of the algorithm in future iterations. Mining the knowledge from one or multiple runs of the algorithm can also be used to improve the algorithm.
We welcome papers illustrating symbiotic developments that bring important advantages to any of the two areas of research.
The topics covered by this workshop contain (but are not limited to):
- Natural Computing enhanced by Data Mining concepts
- Data Mining tasks approached with Natural Computing
- Natural Computing for Big Data analysis
- Evolutionary Machine Learning
- Real world applications

 

 

 Program Committee: Mihaela Breaban, Alexandru Ioan Cuza University of Iasi, Romania
  Elena Bautu, Ovidius University of Constanta, Romania
  Camelia Chira, Technical University of Cluj-Napoca, Romania
  Paul Cotofrei, University of Neuchatel, Switzerland
  Dragos Gavrilut, Alexandru Ioan Cuza University of Iasi, Romania
  Madalina Raschip, University of Neuchatel, Switzerland
  Vlad Radulescu, Alexandru Ioan Cuza University of Iasi, Romania
  Daniel Stamate, Goldsmiths, University of London, UK
  Catalin Stoean, University of Craiova, Romania
  Kilian Stoffel, University of Neuchatel, Switzerland

Probabilistic Models and Metaheuristics for Scheduling

 Co-chairs: Marc Eduard Frincu, University of Southern California, USA 
  Stephane Genaud, ENSIIE Engineering School, France 
  Daniela Zaharie, West University of Timisoara, Romania 

Scheduling and planning problems arises in many real-world contexts with various industrial and economic applications, from job shop scheduling and assembly line balancing to efficient cloud resource provisioning. Identifying good schedules usually leads to difficult optimization problems which involve constraints, multiple conflicting optimization criteria and uncertainty. The presence of uncertainty limits the effectiveness of deterministic models and methods. In the context of scheduling, the probabilistic models can be used as surrogates for evaluate the quality of a solution, can be used to estimate the likelihood of various events which influence the scheduling process or to incorporate prior knowledge about the problem into the search mechanism. On the other hand, the presence of constraints and of multiple optimization criteria limits the effectiveness of exact optimization methods, allowing the metaheuristics to prove their superiority for this class of problems.

The aim of this session is to group original contributions on scalable and robust scheduling metaheuristics based on appropriate probabilistic models and addressing various types of real world applications. Theoretical analyses as well as experimental studies are welcome.

The topics include but are not limited to:

  • scheduling performance measures
  • probabilistic models in scheduling (reliability/failure models, Bayesian networks, etc.)
  • constructive scheduling heuristics versus iterative-improvement heuristics
  • population-based scheduling metaheuristics (e.g. estimation of distribution algorithms, evolutionary algorithms, ant colony optimization, particle swarm optimization etc.)
  • local search based scheduling metaheuristics (tabu search, variable neighborhood search, iterated local search, greedy randomized adaptive search, simulated annealing etc.)
  • hybridization of metaheuristics with various local search heuristics
  • scalability of scheduling algorithms
  • real time scheduling
  • energy aware scheduling
  • applications in cloud computing, job-shop and flow-shop scheduling problems, vehicle routing problems, preventive maintenance scheduling etc.

Complex Networks and Landscape Analysis

Special Track EVOLVE 2015

Michael T. M. Emmerich (Leiden University) and Asep Maulana (Leiden University)

This track focuses on computational methods for complex network analysis and the closely related topic of landscape analysis.

In complex network analysis the subject of study are properties of networks the constituents of which are rather simple, but the dynamics are complex due to emergent behavior. Applications range from biological systems to the study of social networks and parallel processes in computer science. Typical problems are system identification and design, as well as finding explanations for emerging behavior and computational aspects.

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The metaphor of a (fitness) landscape is used in biology and bio-inspired optimization to describe neighborhood systems equipped with one or many potential functions (e.g. fitness, free energy, objective function). The purpose in landscape analysis is to find stable points in biological and chemical systems, characterize problem difficulty in bio-inspired optimization, or to understand evolutionary dynamics. The canonical representation of landscapes in discrete configuration spaces are node-weighted networks, or generalizations of it (such as hypergraphs).

Both topics are closely related: Whereas in the first is more concerned with dynamical aspects the second deals with static analysis of networks. In this track we look for contribution to the topic of complex network and landscape analysis, including:

  1. Computational methods for network identification and analysis
  2. Finding motifs and patterns in large (dynamical) networks
  3. Identification of biological and gene regulatory networks
  4. Neighborhood systems, pre-topologies, and generalizations of graphs
  5. Fast enumeration of networks and trees; combinatorial state space size
  6. Design and optimization of complex networks
  7. Landscape analysis: e.g. adaptive walk statistics, barrier trees, local optima networks,
  8. Community Detection and Graph Clustering
  9. Growth of networks; scale free networks; small worlds;
  10. Real-world applications, e.g. in logistics and bioinformatics

Submissions:

Please submit your contribution before February 1, 2015 (check for updates on website).

Full papers and extended abstracts are possible forms of contribution. Every accepted paper will be orally presented on the EVOLVE 2015 event in Iasi and full papers will be published in the Springer proceedings. Extended abstracts will be published in the short paper proceedings with ISBN/ISSN. All papers will be reviewed in a single-blind review process.  Submission EVOLVE2015, EASYCHAIR via the main system and indicate the track in the submission.

http://www.evolve-conference.org

For questions please send email to Dr. Michael Emmerich (This email address is being protected from spambots. You need JavaScript enabled to view it. ).

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