Mathematical Problems in Engineering

Optimization Algorithms Combining (Meta)heuristics and Mathematical Programming and Its Application in Engineering


Status
Published

1Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile

2Nanyang Technological University, Nanyang, Singapore

3CONICET, Buenos Aires, Argentina


Optimization Algorithms Combining (Meta)heuristics and Mathematical Programming and Its Application in Engineering

Description

Complex optimization problems can be tackled by means of mathematical programming methods as well as by means of (meta)heuristic methods. On the one hand, mathematical programming methods give us guarantee of optimality, while (meta)heuristic methods do not. On the other hand, heuristic methods can handle large and complex optimization problems, while mathematical programming methods tend to fail as the size of the optimization problem in hand increases. Thus, it makes sense to combine these two strategies to obtain better solutions to the problem that is being addressed. During the last two decades or so, algorithms that either include mathematical programming solvers into (meta)heuristic frameworks or include (meta)heuristic concepts within mathematical programming methods have demonstrated to be very effective in solving large complex optimization problems. These hybrid algorithms are also called matheuristics.

The aim of this special issue is to publish high-quality papers that combine (meta)heuristic methods and mathematical programming to solve complex optimization problems. Reviews on this topic are also welcome.

Potential topics include but are not limited to the following:

  • Theoretical issues on matheuristic methods
  • Novel algorithms combining mathematical programming and (meta)heuristics methods
  • Mixed integer programming and (meta)heuristic methods
  • Guided search and mathematical programming
  • Mathematical programming solvers embedded into (meta)heuristic frameworks
  • Hybrid algorithms for big data
  • Hybrid algorithms for deep learning
  • Hybrid algorithms applied to real problems from industry

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 3967457
  • - Editorial

Optimization Algorithms Combining (Meta)heuristics and Mathematical Programming and Its Application in Engineering

Nibaldo Rodríguez | Abhishek Gupta | ... | Guillermo Cabrera-Guerrero
  • Special Issue
  • - Volume 2018
  • - Article ID 6193649
  • - Research Article

A Hybrid Simulated Annealing/Linear Programming Approach for the Cover Printing Problem

Federico Alonso-Pecina | David Romero
  • Special Issue
  • - Volume 2018
  • - Article ID 6303596
  • - Research Article

An Improved Lagrangian Relaxation Algorithm for the Robust Generation Self-Scheduling Problem

Ping Che | Zhenhao Tang | ... | Xiaoli Zhao
  • Special Issue
  • - Volume 2018
  • - Article ID 9248318
  • - Research Article

Multiple-Try Simulated Annealing Algorithm for Global Optimization

Wei Shao | Guangbao Guo
  • Special Issue
  • - Volume 2018
  • - Article ID 8024762
  • - Research Article

Reconstruction of Medical Images Using Artificial Bee Colony Algorithm

Nur ‘Afifah Rusdi | Zainor Ridzuan Yahya | ... | Wan Zuki Azman Wan Muhamad
  • Special Issue
  • - Volume 2018
  • - Article ID 4813030
  • - Research Article

A Three-Term Conjugate Gradient Algorithm with Quadratic Convergence for Unconstrained Optimization Problems

Gaoyi Wu | Yong Li | Gonglin Yuan
  • Special Issue
  • - Volume 2018
  • - Article ID 8087958
  • - Research Article

Local Negative Base Transform and Image Scrambling

Gangqiang Xiong | Shengqian Zheng | ... | Dongxu Qi
  • Special Issue
  • - Volume 2018
  • - Article ID 4607853
  • - Research Article

A Projection Neural Network for Circular Cone Programming

Yaling Zhang | Hongwei Liu
  • Special Issue
  • - Volume 2018
  • - Article ID 3145947
  • - Research Article

A New Generalized Deep Learning Framework Combining Sparse Autoencoder and Taguchi Method for Novel Data Classification and Processing

Ahmad M. Karim | Mehmet S. Güzel | ... | Fatih V. Çelebi
  • Special Issue
  • - Volume 2018
  • - Article ID 7484256
  • - Research Article

An Objective Penalty Function-Based Method for Inequality Constrained Minimization Problem

Shujun Lian | Sitong Meng | Yiju Wang
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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