ICSIBO 2016 - 2016 International Conference on Swarm Intelligence Based Optimization

The aim of this conference is to highlight the theoretical progress of swarm intelligence metaheuristics and their applications.
Swarm intelligence is a computational intelligence technique involving the study of collective behavior in decentralized systems. Such systems are made up of a population of simple individuals interacting locally with one another and with their environment. Although there is generally no centralized control on the behavior of individuals, local interactions among individuals often cause a global pattern to emerge. Examples of such systems can be found in nature, including ant colonies, animal herding, bacteria foraging, bee swarms, and many more. However, swarm intelligence computation and algorithms are not necessarily nature-inspired.
Topics
Topics of interest include but are not limited to:
Theoretical advances of swarm intelligence metaheuristics
Combinatorial, discrete, binary, constrained, multi-objective, multi-modal, dynamic, noisy, and large-scale optimization
Artificial immune systems, particle swarms, ant colony, bacterial foraging, artificial bees, fireflies algorithm
Hybridization of algorithms
Parallel/distributed computing, machine learning, data mining, data clustering, decision making and multi-agent systems based on swarm intelligence principles
Adaptation and applications of swarm intelligence principles to real world problems in various domains, including medicine, biology, chemistry, finance, insurance, economics, social sciences, transportation, tourism, education, defense, telecommunications, energy, management, information retrieval, software engineering, fraud detection, environment, remote-sensing, robots