A Merit Function Approach for Evolution Strategies
Y. Diouane (youssef.diouaneisae.fr)
Abstract: In this paper, we extend a class of globally convergent evolution strategies to handle general constrained optimization problems. The proposed framework handles relaxable constraints using a merit function approach combined with a specific restoration procedure. The unrelaxable constraints in our framework, when present, are treated either by using the extreme barrier function or through a projection approach. The introduced extension guaranties to the regarded class of evolution strategies global convergence properties for first order stationary constraints. Preliminary numerical experiments are carried out on a set of known test problems as well as on a multidisciplinary design optimization problem.
Keywords: Derivative-free optimization, evolution strategies, merit function, global convergence.
Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )
Citation: Tech. Report, ISAE-SUPAERO, 2018.
Entry Submitted: 04/09/2018
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