Mathematical Problems in Engineering

Swarm Intelligence in Engineering


Publishing date
25 Jan 2013
Status
Published
Submission deadline
07 Sep 2012

Guest Editors

1Dalian University of Technology, Dalian, China

2Delft University of Technology, Delft, The Netherlands

3Dalian Maritime University, Dalian, China


Swarm Intelligence in Engineering

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/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2013
  • - Article ID 835251
  • - Editorial

Swarm Intelligence in Engineering

Baozhen Yao | Rui Mu | Bin Yu
  • Special Issue
  • - Volume 2013
  • - Article ID 413565
  • - Research Article

An Improved Harmony Search Based on Teaching-Learning Strategy for Unconstrained Optimization Problems

Shouheng Tuo | Longquan Yong | Tao Zhou
  • Special Issue
  • - Volume 2013
  • - Article ID 948303
  • - Research Article

A Swarm Optimization Algorithm for Multimodal Functions and Its Application in Multicircle Detection

Erik Cuevas | Daniel Zaldívar | Marco Pérez-Cisneros
  • Special Issue
  • - Volume 2013
  • - Article ID 256180
  • - Research Article

Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

Jui-Yu Wu
  • Special Issue
  • - Volume 2013
  • - Article ID 687969
  • - Research Article

Escape-Route Planning of Underground Coal Mine Based on Improved Ant Algorithm

Guangwei Yan | Dandan Feng
  • Special Issue
  • - Volume 2013
  • - Article ID 459503
  • - Research Article

A Constructive Data Classification Version of the Particle Swarm Optimization Algorithm

Alexandre Szabo | Leandro Nunes de Castro
  • Special Issue
  • - Volume 2013
  • - Article ID 409486
  • - Research Article

Particle Swarm Optimization Algorithm for Unrelated Parallel Machine Scheduling with Release Dates

Yang-Kuei Lin
  • Special Issue
  • - Volume 2013
  • - Article ID 765135
  • - Research Article

Dynamic Route Guidance Using Improved Genetic Algorithms

Zhanke Yu | Mingfang Ni | ... | Yanhua Zhang
  • Special Issue
  • - Volume 2013
  • - Article ID 302627
  • - Research Article

A Hybrid Algorithm of Traffic Accident Data Mining on Cause Analysis

Jianfeng Xi | Zhenhai Gao | ... | Guobao Ning
  • Special Issue
  • - Volume 2013
  • - Article ID 175848
  • - Research Article

Improved Barebones Particle Swarm Optimization with Neighborhood Search and Its Application on Ship Design

Jingzheng Yao | Duanfeng Han
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate27%
Submission to final decision64 days
Acceptance to publication34 days
CiteScore1.800
Impact Factor1.009
 Submit

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.