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Tutorial Constraint-Handling in Nature-Inspired Optimization

Constraint-Handling in Nature-Inspired Optimization

Efrén Mezura-Montes
Professor of Artificial Intelligence Department
Veracruz University, México



Abstract:

Evolutionary algorithms and, more recently, swarm intelligence algorithms have become a popular option to solve complex optimization problems where classic optimization techniques are unable to provide competitive results. However, such algorithms were designed to deal with unconstrained search spaces. Therefore, constraint-handling techniques must be designed and coupled to the algorithms to consider the feasibility of solutions in the search process. Choosing a suitable constraint-handling technique for a given nature-inspired algorithm is an open problem.

This tutorial firstly motivates the usage of alternative optimization approaches such as nature-inspired algorithms and introduces the constrained numerical optimization problem. Thereafter, a review of those constraint-handling techniques used in the early years of the area (mostly penalty functions and decoders) is presented, while those more popular in the recent years (feasibility rules, multi-objective optimization concepts and ε-constraint, among others) are detailed afterwards. A discussion about which nature-inspired algorithms have been more preferred in the area is also considered at this point of the tutorial. Finally, the current and future trends on constrained numerical optimization problems are presented.

Expected enrollment:

Researchers, practitioners and students interested in numerical optimization and its applications, e.g., mechanical design, electronic design, power dispatch optimization, among others.

 

Biography:

Dr. Efrén Mezura-Montes is a full-time researcher at the Artificial Intelligence Department in Veracruz University in Xalapa, Veracruz, MEXICO. His research interests are the design, analysis and application of bio-inspired algorithms to solve complex optimization problems. He has published over 70 papers in peer-reviewed journals and conferences. He also has one edited book published by Springer and six book chapters published by international publishing companies.

Dr. Mezura-Montes was the founder of the IEEE-CIS Task Force on Nature-Inspired Constrained Optimization and he is a member of the IEEE-CIS Evolutionary Computation Technical Committee. He is also a member of the editorial board of the International Journal of Natural Computing Research, the International Journal of Energy Optimization and Engineering and the journal Artificial Intelligence Research. He is also a reviewer for more than 20 international specialized journals. Dr. Mezura-Montes is a Level 1 member of the Mexican National Researchers System (SNI).

 

The length of the tutorial:
two hours.

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