Abstract
This paper studies the application of genetic algorithms to the construction of exact D-optimal experimental designs. The concept of genetic algorithms is introduced in the general context of the problem of finding optimal designs. The algorithm is then applied specifically to finding exact D-optimal designs for three different types of model. The performance of genetic algorithms is compared with that of the modified Fedorov algorithm in terms of computing time and relative efficiency. Finally, potential applications of genetic algorithms to other optimality criteria and to other types of model are discussed, along with some open problems for possible future research.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
