Solving constrained global optimization problems without penalty parameters
Purpose - To propose a new method for solving constrained global optimization problems using a method that consists of transforming a constrained global optimization problem into an unconstrained one without using any penalty coefficients. Design/methodology/approach - Use of an unconstrained global optimization method such as the Alienor method which has been adapted for several variables. Findings - Use of the adapted Alienor method allowed the solution of the transformed problem with little difficulty. Research limitations/implications - Transforms the original objective function into a new one involves the introduction of some extra parameters. Cannot guarantee the convergence to a global solution of the original problem. The simple described approach, provides new possibilities. Practical implications - No further parameters introduced in this new approach, and no conditions or hypotheses are imposed on the objective function or on the constraints. Originality/value - New method of transforming a constrained problem into an unconstrained one, with use of proven Alienor method adapted to several variables.
cybernetics optimization techniques numerical analysis