A memetic approach to the solution of constrained min-max problems

Filippi, Gianluca and Vasile, Massimiliano (2019) A memetic approach to the solution of constrained min-max problems. In: 2019 IEEE Congress on Evolutionary Computation, 2019-06-10 - 2019-06-13.

Preview

Text (Filippi-Vasile-CEC-2019-A-memetic-approach-to-the-solution-of-constrained)
Filippi_Vasile_CEC_2019_A_memetic_approach_to_the_solution_of_constrained.pdf
Accepted Author Manuscript
Download (769kB)| Preview

Abstract

This paper proposes a novel memetic algorithm for the solution of constrained min-max problems that derive from the optimal design of complex systems under worst-case conditions. In this context the maximisation of a quantity of interest over the space of uncertain variables is required to identify the worst-case scenario (or worst-case solution under uncertainty). An optimal design vector is then identified such that the worst-case value of the quantity of interest is minimised. In the most general case, both maximisation and minimisation are subject to strict feasibility constraints. The ultimate goal of the minimisation problem is to identify the design solution that is feasible for all possible values of the uncertain parameters.

Author(s):	Filippi, Gianluca and Vasile, Massimiliano ORCID: https://orcid.org/0000-0001-8302-6465
Item type:	Conference or Workshop Item(Paper)
ID code:	68668
Keywords:	worst case scenario, min-max, epistemic uncertainty, benchmark, Mechanical engineering and machinery, Mechanical Engineering
Subjects:	Technology > Mechanical engineering and machinery
Department:	Faculty of Engineering > Mechanical and Aerospace Engineering Strategic Research Themes > Ocean, Air and Space Technology and Innovation Centre > Advanced Engineering and Manufacturing
Depositing user:	Pure Administrator
Date deposited:	02 Jul 2019 10:11
Last modified:	12 Nov 2019 01:38
Related URLs:	Event
URI:	https://strathprints.strath.ac.uk/id/eprint/68668
Export data:

CORE (COnnecting REpositories)