Multiobjective genetic algorithms with application to control engineering problems.
Carlos M. Fonseca · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · 1995
Constraint handling with genetic algorithms is then developed from a decision making perspective and characterized, with application to control system design in mind. Related genetic algorithm issues, such as the ability to maintain diverse solutions along the trade-off surface and responsiveness to on-line changes in decision policy, are also considered. The application of the multiobjective GA to three realistic problems in optimal controller design and non-linear system identification demonstrates the ability of the approach to concurrently produce many good compromise solutions in a single run, while making use of any preference information interactively supplied by a human decision maker. The generality of the approach is made clear by the very different nature of the two classes of problems considered. i Acknowledgements I would like to thank my supervisor Professor Peter Fleming for his help, support, and encouragement throughout this research programme. Thanks