The Scientific World Journal

Swarm Intelligence and Its Applications 2014


Publishing date
02 May 2014
Status
Published
Submission deadline
21 Feb 2014

1School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China

2Anand International College of Engineering, Near Kanota, Agra Road, Jaipur, India

3Ambedkar Institute of Advanced Communication Technologies and Research, New Delhi, India

4Department of Electrical Engineering, Islamic Azad University, Gonabad Branch, Gonabad, Iran

5Brain Image Processing, Columbia University, New York, NY, USA


Swarm Intelligence and Its Applications 2014

Description

Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial. SI systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environments. The inspiration often comes from nature, especially biological systems. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of “intelligent” global behavior, being unknown to the individual agents. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling.

Recently, SI algorithms have attracted close attention of researchers and have also been applied successfully to solve optimization problems in engineering. Nevertheless, for large and complex problems, SI algorithms consume considerable computation time due to stochastic feature of the search approaches. Therefore, there is a potential requirement for developing efficient algorithm to find solutions under the limited resources, time, and money in real-world applications.

The aim of this special issue is to highlight the most significant recent developments on the topics of SI and to apply SI algorithms in real-life scenario. Contributions containing new insights and findings in this field are welcome. Particular attention will be given to the following theme areas; however, it should be stressed that a broad range of submissions are encouraged. We invite authors to contribute with original research articles as well as review articles to this special issue. Potential topics include, but are not limited to:

  • Convergence proof for SI algorithms
  • Benchmarking and evaluation of new SI algorithms
  • Comparative, theoretical, and empirical studies on SI algorithms (e.g., artificial bee optimization, ant colony optimization, artificial fish algorithm, artificial immune system, bat algorithm, bacterial foraging optimization, cuckoo search, firefly algorithm, intelligent water drops, magnetic optimization algorithm, and particle swarm optimization)
  • SI algorithms for real-world applications (e.g., aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, image processing, industrial engineering and manufacturing systems, mechanical engineering, signal processing, etc.)

Before submission authors should carefully read over the journal’s Author Guidelines, which are located at http://www.hindawi.com/journals/tswj/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/tswj/computer.science/sia14/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2014
  • - Article ID 204294
  • - Editorial

Swarm Intelligence and Its Applications 2014

Yudong Zhang | Praveen Agarwal | ... | Xuewu Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 136920
  • - Research Article

Bare-Bones Teaching-Learning-Based Optimization

Feng Zou | Lei Wang | ... | Hongye Li
  • Special Issue
  • - Volume 2014
  • - Article ID 164053
  • - Research Article

Minimum Variance Distortionless Response Beamformer with Enhanced Nulling Level Control via Dynamic Mutated Artificial Immune System

Tiong Sieh Kiong | S. Balasem Salem | ... | Soodabeh Darzi
  • Special Issue
  • - Volume 2014
  • - Article ID 672983
  • - Research Article

Hybrid Biogeography-Based Optimization for Integer Programming

Zhi-Cheng Wang | Xiao-Bei Wu
  • Special Issue
  • - Volume 2014
  • - Article ID 271895
  • - Research Article

A Graph-Based Ant Colony Optimization Approach for Process Planning

JinFeng Wang | XiaoLiang Fan | Shuting Wan
  • Special Issue
  • - Volume 2014
  • - Article ID 973093
  • - Research Article

The Contribution of Particle Swarm Optimization to Three-Dimensional Slope Stability Analysis

Roohollah Kalatehjari | Ahmad Safuan A Rashid | ... | Mohsen Hajihassani
  • Special Issue
  • - Volume 2014
  • - Article ID 746260
  • - Research Article

Path Planning Using a Hybrid Evolutionary Algorithm Based on Tree Structure Encoding

Ming-Yi Ju | Siao-En Wang | Jian-Horn Guo
  • Special Issue
  • - Volume 2014
  • - Article ID 413265
  • - Research Article

Two-Cloud-Servers-Assisted Secure Outsourcing Multiparty Computation

Yi Sun | Qiaoyan Wen | ... | Wenmin Li
  • Special Issue
  • - Volume 2014
  • - Article ID 232714
  • - Research Article

Constrained Multiobjective Biogeography Optimization Algorithm

Hongwei Mo | Zhidan Xu | ... | Haiping Ma
  • Special Issue
  • - Volume 2014
  • - Article ID 375358
  • - Research Article

An Improved Cockroach Swarm Optimization

I. C. Obagbuwa | A. O. Adewumi
The Scientific World Journal
 Journal metrics
Acceptance rate23%
Submission to final decision56 days
Acceptance to publication61 days
CiteScore1.430
Impact Factor-
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