Abstract
Design is a process of constraint identification and satisfaction. The process of constraint satisfaction is complex, because coupling between the constraints hinders the process of searching for a feasible design. This paper presents computational methods to aid designers by automatically searching for a feasible design, subject to a set of highly coupled, non-linear, equality and inequality constraints. The tools combine symbolic methods, adaptive searches (genetic algorithms and simulated annealing), and methods to incorporate knowledge of the constraints into the search process. The paper concludes with a comparison of two approaches: one using simulated annealing and one using genetic algorithms. The author found that including knowledge of the constraint space into the adaptive searches significantly improved the efficiency of the search process over the simple, untailored application of the methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Engineering Applications of Artificial Intelligence
Disclaimer: 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.