Mathematical Problems in Engineering

Hybrid Intelligent Techniques for Benchmark Functions and Real-World Optimization Problems


Status
Published

Lead Editor

1Département Génie Electrique, Institut National des Sciences Appliquées de Lyon, Villeurbanne, France

2School of Computer Science Engineering, Kyungpook National University, Daegu, Republic of Korea

3Key Laboratory of Intelligent Perception and Image, Xidian University, Xi'an, China

4Department of Electronics & Communication Engineering, Anna University, Chennai, India


Hybrid Intelligent Techniques for Benchmark Functions and Real-World Optimization Problems

Description

In the recent past, metaheuristics have been developed to solve a wide range of optimization problems in various fields of engineering and science. Some representative examples, such as genetic algorithms, particle swarm optimization, and artificial bee colony, are used to solve many hard optimization problems effectively and establish powerful search capabilities for solving such problems. In spite of these advantages, these metaheuristics still encounter challenges when solving real-world and large scale optimization problems, forcing the development of new solution procedures whose efficiency is measured by their ability to find acceptable solutions within a reasonable computational expense.

Hybrid intelligence is recognized as an integration of different metaheuristic approaches and thoughts to overcome individual limitations and achieve synergistic effects. Such hybridizations can be used to take the advantage of strengths from different intelligent techniques and overcome the difficulties of the metaheuristics when applied to solve the problems individually.

The aim of this special issue is to archive the innovative advancements and mathematical modeling of hybrid intelligence for handling complex optimization problems, which may depend largely on methods from computational intelligence and operations research. This special issue is a forum for researchers to review and disseminate quality research on hybrid intelligent techniques with emphasis on mathematical modeling and analysis of algorithms with applications in the context of engineering and science. Potential topics include, but are not limited to:

  • Mathematical modeling and evaluation of new hybrid intelligent techniques based on:
    • modular integration of two or more metaheuristics, retaining the identity of each methodology
    • fusion: transforming the knowledge representation in one methodology into another form of representation to another methodology
  • Theoretical and technological advancements in mathematical methods for hybrid intelligent techniques, with validation through convincing computational experiments, comparison, and convergence proof
  • Application of hybrid intelligent techniques for real-world and large scale optimization problems (all fields of engineering and science)

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/hitt/ according to the following timetable:


Articles

  • Special Issue
  • - Volume 2015
  • - Article ID 617685
  • - Research Article

A Hybrid Intelligent Search Algorithm for Automatic Test Data Generation

Ying Xing | Yun-Zhan Gong | ... | Xu-Zhou Zhang
  • Special Issue
  • - Volume 2015
  • - Article ID 862145
  • - Research Article

Multiconstrained QoS Routing Using a Differentially Guided Krill Herd Algorithm in Mobile Ad Hoc Networks

D. Kalaiselvi | R. Radhakrishnan
  • Special Issue
  • - Volume 2014
  • - Article ID 260869
  • - Research Article

A Two-Stage Algorithm for the Closed-Loop Location-Inventory Problem Model Considering Returns in E-Commerce

Yanhui Li | Mengmeng Lu | Bailing Liu
  • Special Issue
  • - Volume 2014
  • - Article ID 867645
  • - Research Article

A Double Evolutionary Pool Memetic Algorithm for Examination Timetabling Problems

Yu Lei | Maoguo Gong | ... | Qing Cai
  • Special Issue
  • - Volume 2014
  • - Article ID 309327
  • - Research Article

Design Optimization of Mechanical Components Using an Enhanced Teaching-Learning Based Optimization Algorithm with Differential Operator

B. Thamaraikannan | V. Thirunavukkarasu
  • Special Issue
  • - Volume 2014
  • - Article ID 804310
  • - Research Article

Ant Colony Algorithm and Simulation for Robust Airport Gate Assignment

Hui Zhao | Liqin Cheng
  • Special Issue
  • - Volume 2014
  • - Article ID 836524
  • - Research Article

Reactive GTS Allocation Protocol for Sporadic Events Using the IEEE 802.15.4

Mukhtar Azeem | Majid I. Khan | ... | Mansoor Ahmed
  • Special Issue
  • - Volume 2014
  • - Article ID 291581
  • - Research Article

A Hybrid DE-RGSO-ELM for Brain Tumor Tissue Categorization in 3D Magnetic Resonance Images

K. Kothavari | B. Arunadevi | S. N. Deepa
  • Special Issue
  • - Volume 2014
  • - Article ID 103059
  • - Research Article

A Tabu Search-Based Memetic Algorithm for Hardware/Software Partitioning

Geng Lin | Wenxing Zhu | M. Montaz Ali
  • Special Issue
  • - Volume 2014
  • - Article ID 173068
  • - Research Article

An Optimized Network Selection and Handover Triggering Scheme for Heterogeneous Self-Organized Wireless Networks

Murad Khan | Kijun Han
Mathematical Problems in Engineering
 Journal metrics
Acceptance rate26%
Submission to final decision70 days
Acceptance to publication37 days
CiteScore1.800
Impact Factor1.009
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