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 forging, 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.
