Differential Evolution and Large-Scale Optimization Applications

Differential Evolution and Large-Scale Optimization Applications

Aleš Zamuda
Release Date: April, 2016|Copyright: © 2016 |Runtime: 2 hrs 21 mins
EISBN13: 9781522507291|DOI: 10.4018/978-1-5225-0729-1

Description

Differential Evolution (DE) is one of the most popular, high-performance optimization algorithms with variants that have been outperforming others for years. As a result, DE has grown to accommodate wide usage for a variety of disciplines across scientific fields.

Differential Evolution and Large-Scale Optimization Applications presents a research-based overview and cross-disciplinary applications of optimization algorithms. Emphasizing applications of Differential Evolution (DE) across sectors and laying the foundation for further use of DE algorithms in real-world settings, this video is an essential resource for researchers, engineers, and graduate-level students.

Topics Covered

  • Algorithms
  • Optimization
  • Parallel Differential Evolution
  • Performance Improvement
  • Stochastic Methods
  • Tree Model Reconstruction

Table of Contents

Differential Evolution and Large-Scale Optimization Applications
2:10 mins
Section 1:Differential Evolution
 
Lesson 1:Explaining Differential Evolution
8:33 mins
 
Lesson 2:Improvements to Differential Evolution
12:02 mins
 
Lesson 3:Benchmarks of Differential Evolution
15:58 mins
 
Section 2:Application of DE to Tree Model Reconstruction
 
Lesson 4:Procedural Tree Models in Tree Model Reconstruction
7:28 mins
 
Lesson 5:Automatic Modeling of Trees Using Differential Evolution
11:29 mins
 
Lesson 6:Reconstructing Trees from Images Using Differential Evolution
11:49 mins
 
Section 3:Application of Differential Evolution in Underwater Glider Path Planning
 
Lesson 7:Solving Underwater Robotics Challenges with Differential Evolution
5:54 mins
 
Lesson 8:Planning Glider Paths using Differential Evolution
6:27 mins
 
Lesson 9:Differential Evolution Performance Comparison
11:04 mins
 
Section 4:Application of Differential Evolution in Hydro and Thermal Power Plant Scheduling
 
Lesson 10:Hydro-Thermal Scheduling using Differential Evolution
9:58 mins
 
Lesson 11:Parallel Differential Evolution
6:39 mins
 
Lesson 12:Surrogate Differential Evolution
12:05 mins
 
Section 5:Applications of Differential Evolution in Real World Industrial Challenges
 
Lesson 13:CEC 2011 Benchmarks of Differential Evolution
6:39 mins
 
Lesson 14:Open Issues of Differential Evolution
5:45 mins
 
Lesson 15:Forthcoming Challenges of Differential Evolution
7:58 mins
 

Reviews and Testimonials

I highly recommend this material because of its overall quality and the author’s actual interest. Zamuda demonstrates a deep theoretical knowledge of the matter, while, at the same time, describes in first person practical applications that he has successfully developed.

– Dr. Daniel Hernández, School of Computer Engineering, University of Las Palmas de Gran Canara, Spain

Highly recommended. The lecturer has long term experience with the topics and is keen to share his experience, not just general knowledge about Differential Evolution.

– Professor Ferrante Neri, De Montfort University, UK

These lectures offer a nice and rather comprehensive overview of the applicative potential of population-based metaheuristics with a focus on differential evolution. The author has extensive experience in using and developing differential evolution algorithms, and this experience has allowed him to deliver a well-structured and convincing video series. Highly Recommended.

– Professor Daniela Zaharie, Department of Computer Science, West University of Timisoara, Romania

I highly recommend this video lecture series. In my opinion, there are no weaknesses in the content and organization of the video. Students from all over the world who study global optimization and evolutionary algorithms, especially differential evolution algorithms, can greatly benefit from this series.

– Radka Polakova, University of Ostrava, Czech Republic

Highly Recommended: differential evolution is nowadays one of the most popular evolutionary algorithms. This well-prepared material by Dr. Zamuda provides basic information about the algorithm as well as detailed applications in diverse domains.

– Dr. Efrén Mezura-Montes, Artificial Intelligence Research Center, University of Veracruz, Mexico

Dr. Zamuda is an internationally-renowned expert in differential evolution (DE). Dr. Zamuda has not only utilized DE in a diverse range of application domains, but has also significantly contributed to its success. In this video lecture, Dr. Zamuda provides an invaluable overview of the brief history and of ongoing research efforts in the field of DE. Clearly, the video lecture's target audience has a solid background in computer science or related fields and is interested in gaining new insights in state-of-the-art optimization techniques.

– Dr. Sebastian von Mammen, Universität Augsburg, Germany