Systematic Design and Application of Metaheuristics

Besides learning how to apply metaheuristics, the interactive 4-day course deals with the following questions:

1. How to systematically choose among different metaheuristics based on the properties of the problem that should be solved?
2. How to systematically design efficient and high-performing metaheuristics?
3. How to consider problem-specific knowledge for the design of metaheuristics?

Metaheuristics like evolutionary algorithms, genetic programming, variable neighborhood search, tabu search, simulated annealing, and others are applied to large, difficult, or realistic optimization problems, for which efficient classical optimization methods are not available or applicable. This includes the optimization of other AI systems like neural networks.  Many text books teach such methods by providing detailed descriptions of the functionality of single examples of metaheuristics neglecting the underlying and common concepts. As a result, the systematic design and application of metaheuristics is often not a systematic engineering task but a result of repeated trial and error. Applicants apply textbook approaches and are surprised that they do not perform well when used for problems of realistic size or complexity. This course at hand takes a different approach. It teaches the basic, method-independent principles and design guidelines of metaheuristics and how they can be used to systematically develop superior heuristic optimization methods for problems of choice. Consequently, the course focuses on the application side and answers three fundamental questions:

1. It tells the participants on which problems metaheuristics are expected to perform well, and what are problems where other optimization paradigms are a better choice.
2. Participants learn to systematically design an appropriate metaheuristic for a particular problem using a coherent view on design elements and working principles of metaheuristics. 
3. Participants learn how to make use of problem-specific knowledge for the design of efficient and effective metaheuristics that solve not only small toy problems but also perform well on large and real-world problems.

Date:

7. - 10. Oktober 2024

Course Language:

English

Location:

Johannes Gutenberg-University Mainz
Haus Recht und Wirtschaft II
Jakob-Welder-Weg 4
55128 Mainz
Raum 00-341 (HS VII)

Lecturer:

Registration:

Click for information on fees, payment and registration,

or email us: prodok@vhbonline.org.

Registration deadline: 8. September 2024