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Unified approach for solving Box-Constrained models with continuous or discrete variables by Non monotonous Derivative Free Optimization techniques.

Ubaldo M Garcia Palomares(ubaldo***at***gti.uvigo.es)
Pedro S Rodríguez Hernández(pedro***at***uvigo.es)

Abstract: This paper describes a unified approach for solving Box-Constrained Optimization Problems (BCOP) in Euclidian spaces. The variables may be either continuous or discrete; in which case, they range on a grid of isolated points regularly spaced. For the continuous case, convergence is shown under standard assumptions; for the discrete case, slight modifications ensure that the algorithm stops in a finite time. Moreover, function evaluations are carried out only on feasible points on the grid, avoiding spurious computations on non feasible points. The paper describes a pseudo code and a preliminary code is written in C, which is applied to small models that have been suggested in the open literature.

Keywords: DFO, discrete variables, non monotone

Category 1: Nonlinear Optimization (Bound-constrained Optimization )

Category 2: Integer Programming (Other )

Category 3: Optimization Software and Modeling Systems (Problem Solving Environments )

Citation: Unpublished report, Universidade de Vigo, GTI Research group, Dec. 2016. Submitted

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Entry Submitted: 12/12/2016
Entry Accepted: 12/12/2016
Entry Last Modified: 12/12/2016

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