z-logo
open-access-imgOpen Access
Comparison of Evolutionary Algorithms for design optimization
Author(s) -
Wilfried Jakob,
M. Gorges-Schleuter,
Ingo Sieber
Publication year - 1998
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-65078-4
DOI - 10.1007/bfb0056933
Subject(s) - computer science , microelectronics , microsystem , genetic algorithm , evolutionary algorithm , motion planning , task (project management) , process (computing) , optimization problem , algorithm , computer engineering , robot , artificial intelligence , engineering , systems engineering , machine learning , electrical engineering , nanotechnology , materials science , operating system
The production of specimen for microsystems or microcomponents is both, time and material-consuming. In a traditional design process the number of possible variations which can be considered is very limited. Thus, in micro-system technology computer-based design techniques become more and more important — similar to the development of microelectronics. In this paper we compare Evolutionary Algorithms based on Evolution Strategies and the extended Genetic Algorithm GLEAM for solving the design optimization problem. The reference problem is the design optimization of a 2-lens-system being part of a heterodyne receiver, a microoptical communication module. As this is a real world problem, the design must be as insensitive to fabrication tolerances as possible. The results obtained are compared to a more complex task: the robot path planning problem.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom