Preface

Excerpt

As a branch of meta-heuristic algorithms, swarm intelligence is to study the collective behavior of decentralized, self-organized and populated systems. Inspired by the behavior of biological swarms or artificial populations, researchers and practitioners have proposed many distributed models or algorithms for problem-solving in complex environments by means of observing, abstracting, modeling, and simulating the collaborative behavior in nature biological or artificial populations. Usually, the optimization process of a swarm intelligence algorithm is a heuristic and iterative search process by constantly generating, updating, and selecting solutions. The research objective of swarm intelligence algorithm is to design and develop optimization algorithms with the ability of problem-solving by taking inspiration from intelligent behaviors exhibited in biological communities and understanding the characteristics of the interaction mechanism in a swarm. Exploring the wisdom of collective behavior of swarm intelligence algorithms have achieved a great success in many practical problems, such as path planning, task scheduling, multi-robot systems, data mining and so on. Currently, swarm intelligence algorithms and their applications are very attractive and widely studied in the community of computational intelligence. …