Menu:



Latest news:

September 15, 2014:
Photos from the conference

September 5, 2014:
IDC 2014 is over

July 2, 2014:
List of accepted papers

May 28, 2014:
Registration is open

March 10, 2014:
Accepted Special Issue on Intelligent Distributed Processing Methods for Big Data.

March 4, 2014:
Paper submission deadline extended, check the new dates.

February 20, 2014:
Accepted Workshop: WSRL 2014.

February 7, 2014:
Accepted Workshop: MASTS 2014.

December 13, 2013:
Accepted Special Issue on Intelligent Distributed Computing.

October 29, 2013:
Accepted Special Issue on International Journal of Bio-Inspired Computation.

October 9, 2013:
Invited speakers: Thomas Stützle and JJ Merelo.

June 11, 2013:
IDC'2014 symposium Web site was launched.

Invited Speakers


Thomas Stützle Université Libre de Bruxelles (ULB)
Title: Automated Algorithm Configuration: Advances and Prospects

Abstract

The design and configuration of optimization algorithms for computationally hard problems is a time-consuming and difficult task. This is mainly This is in large part due to a number of aggravating circumstances such as the NP-hardness of most of the problems to be solved, the difficulty of algorithm analysis due to stochasticity and heuristic biases, and the large number of degrees of freedom in defining and selecting algorithmic components and settings of numerical parameters. Over the recent years, the development of automatic methods to search large configuration spaces has received significant attention as a possible solution to these challenges. Such automatic algorithm configuration methods have by now proved to be instrumental for developing high-performance algorithms.
The presentation will discuss how automatic algorithm configuration tools can be used to develop high-performing evolutionary and other optimization algorithms. After an overview of available tools, I will highlight various successful applications of these such as the automatic configuration of multi-objective optimizers, and the automatic configuration of hybrid stochastic local search algorithms. Finally, I will highlight the impact automatic algorithm configuration has and will have on the algorithm design and development process.



Juan Julián Merelo University of Granada, Spain
Title: Low or no cost distributed evolutionary computation

Abstract

From the era of big science we have back to the "do it yourself" era of science, where you don't have any money to buy clusters and subscribe to grids but still have algorithms that crave many computing nodes and need them for scalability. Fortunately, this coincides with the era of big data, cloud computing, and browsers including JavaScript virtual machines. This talk will concentrate on two different aspects of volunteer or freeriding computing: first, the pragmatic: where to find those resources, which can be used, what kind of support you have to give them; and then, the theoretical: how algorithms can be adapted to a environment in which nodes come and go, have different computing capabilites and operate in complete asynchrony of each other.