Mathematical Problems in Engineering

Swarm Intelligence in Engineering 2014


Publishing date
24 Oct 2014
Status
Published
Submission deadline
06 Jun 2014

1Dalian University of Technology, Dalian, China

2Jilin University, Changchun 130022, China

3Dalian Maritime University, Dalian 116024, China

4Faculty of Technology, Policy and Management, Delft University of Technology, Delft, The Netherlands


Swarm Intelligence in Engineering 2014

Description

Swarm intelligence (SI) is an artificial intelligence technique based on the study of behavior of simple individuals (e.g., ant colonies, bird flocking, animal herding, and honey bees) in various decentralized systems. The population, which consists of simple individuals, can usually solve complex tasks in nature by individuals interacting locally with one another and with their environment. Although their behaviors are primarily characterized by autonomy, distributed functioning, and self-organizing capacities, local interactions among the individuals often cause a global optimal.

Recently, SI algorithms have attracted much attention of researchers and have also been applied successfully to solve optimization problems in engineering. However, for large and complex problems, SI algorithms consume often much computation time due to stochastic feature of the search approaches. Therefore, there is a potential requirement to develop 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. Potential topics include, but are not limited to:

  • Benchmarking and evaluation of new SI algorithms
  • Convergence proof for SI algorithms
  • Comparative theoretical and empirical studies on SI algorithms (e.g., ant colony optimization, particle swarm optimization, artificial bee swarm algorithm, bacterial foraging optimization, and artificial fish algorithm)
  • SI algorithms for real-world applications (e.g., aerospace engineering, bioengineering, chemical engineering, computer engineering, electrical engineering, industrial engineering and manufacturing systems, and mechanical engineering)

Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/mpe/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/mpe/sie14/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2014
  • - Article ID 864586
  • - Research Article

Artificial Intelligence Mechanisms on Interactive Modified Simplex Method with Desirability Function for Optimising Surface Lapping Process

Pongchanun Luangpaiboon | Sitthikorn Duangkaew
  • Special Issue
  • - Volume 2014
  • - Article ID 712417
  • - Research Article

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Jianzhou Wang | Shiqiang Jin | ... | Haiyan Jiang
  • Special Issue
  • - Volume 2014
  • - Article ID 432654
  • - Research Article

A Modified Artificial Bee Colony Algorithm Based on Search Space Division and Disruptive Selection Strategy

Zhen-an He | Caiwen Ma | ... | Huinan Guo
  • Special Issue
  • - Volume 2014
  • - Article ID 187370
  • - Research Article

PSO-Based Robot Path Planning for Multisurvivor Rescue in Limited Survival Time

N. Geng | D. W. Gong | Y. Zhang
  • Special Issue
  • - Volume 2014
  • - Article ID 453564
  • - Research Article

Location Prediction-Based Data Dissemination Using Swarm Intelligence in Opportunistic Cognitive Networks

Jie Li | Xingwei Wang | ... | Zhijie Zhao
  • Special Issue
  • - Volume 2014
  • - Article ID 239130
  • - Research Article

Research of Ant Colony Optimized Adaptive Control Strategy for Hybrid Electric Vehicle

Linhui Li | Haiyang Huang | ... | Ning’an Zheng
  • Special Issue
  • - Volume 2014
  • - Article ID 592682
  • - Research Article

Quantum Behaved Particle Swarm Optimization Algorithm Based on Artificial Fish Swarm

Dong Yumin | Zhao Li
  • Special Issue
  • - Volume 2014
  • - Article ID 640925
  • - Research Article

Damage Identification of Bridge Based on Modal Flexibility and Neural Network Improved by Particle Swarm Optimization

Hanbing Liu | Gang Song | ... | Xianqiang Wang
  • Special Issue
  • - Volume 2014
  • - Article ID 461062
  • - Research Article

A Swarm Random Walk Based Method for the Standard Cell Placement Problem

Najwa Altwaijry | Mohamed El Bachir Menai
  • Special Issue
  • - Volume 2014
  • - Article ID 136753
  • - Research Article

Core Business Selection Based on Ant Colony Clustering Algorithm

Yu Lan | Yan Bo | Yao Baozhen
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Impact Factor1.009
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