GECCO'14: Ant Colony Optimization and Swarm Intelligence track

Marco A. Montes de Oca mmontes at math.udel.edu
Mo Sep 2 17:26:18 CEST 2013


** Apologies for multiple postings **

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**                          CALL FOR PAPERS                          **
** 2014 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO-2014) **
**    ANT COLONY OPTIMIZATION AND SWARM INTELLIGENCE (ACO-SI) TRACK  **
**             July 12-16, 2014, Vancouver, BC, Canada               **
**                       Organized by ACM SIGEVO                     **
**                   http://www.sigevo.org/gecco-2014                **
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Track Description

Swarm Intelligence (SI) is the collective problem-solving behavior of 
groups of animals or artificial agents that results from the local 
interactions of the individuals with each other and with their 
environment. SI systems rely on certain key principles such as 
decentralization, stigmergy, and self-organization. Since these 
principles are observed in the organization of social insect colonies 
and other animal aggregates, such as bird flocks or fish schools, SI 
systems are typically inspired by these natural systems. 

The two main application areas of SI have been optimization and 
robotics. In the first category, Ant Colony Optimization (ACO) and 
Particle Swarm Optimization (PSO) constitute two of the most popular 
SI optimization techniques with numerous applications in science and 
engineering. Other prevailing approaches include Honey Bee 
Optimization, Bacterial Foraging, Firefly Optimization, as well as 
approaches based on specialized behaviors of social insect 
communities. In the second category, SI has been successfully used to 
control large numbers of robots in a decentralized way, which 
increases the flexibility, robustness, and fault-tolerance of the 
resulting systems.

Scope

The ACO-SI Track welcomes submissions of original and unpublished work 
in all experimental and theoretical aspects of SI, including (but not 
limited to) the following areas:

* Biological foundations
* Modeling and analysis of new approaches
* Hybrid schemes with other algorithms
* Combinations with local search techniques
* Constraint-handling and penalty function approaches
* Benchmarking and new empirical results
* Parallel/distributed implementations and applications
* Large-scale applications
* Applications in multi-objective, dynamic, and noisy problems
* Applications in continuous and discrete search spaces
* Multi-swarm and self-adaptive approaches
* Software and high-performance implementations
* Theoretical and experimental research in swarm robotics systems

Each paper will be rigorously evaluated in a double-blind review
process. 
All accepted papers will be published in the ACM Digital Library.

Important Dates:

* Abstract submission: January 15, 2014
* Submission of full papers: January 29, 2014 (strict deadline!)
* Notification of paper acceptance: March 12, 2014
* Camera ready submission: April 14, 2014
* Conference: July 12-16, 2014

Track Chairs:

Dr. Marco A. Montes de Oca (University of Delaware, USA)
http://www.math.udel.edu/~mmontes

Dr. Konstantinos E. Parsopoulos (University of Ioannina, Greece)
http://www.cs.uoi.gr/~kostasp
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