Abstract
This paper presents a constraint multi-objective artificial physics optimisation (CMOAPO) algorithm by introducing a novel optimisation paradigm called artificial physics optimisation (APO) into constraint multi-objective domain. Combining with characteristics of constraint multi-objective optimisation problems, a method of virtual force decreasing is incorporated into CMOAPO to decrease the probability of individuals moving from feasible region into infeasible region. Furthermore, the convergence of CMOAPO is analysed in terms of theory with related knowledge of probability. The performance of CMOAPO algorithm is tested using several benchmark functions. The results obtained show that the proposed approach is effective.
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 callMore From: International Journal of Innovative Computing and Applications
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.
