A Derivative-Free Trust Region Algorithm with Nonmonotone Filter Technique for Bound Constrained Optimization

• Published in: Mathematical problems in engineering Vol. 2018; no. 2018; pp. 1 - 13
• Main Authors: Gao, Jing, Yang, Yueting, Cao, Jian
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 01.01.2018; Hindawi; John Wiley & Sons, Inc
• Subjects: Algorithms; Applied mathematics; Computing time; Mathematical problems; Mathematical programming; Methods; Nonlinear programming; Optimization; Optimization techniques; Parameter identification; Software
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2018/5049027

We propose a derivative-free trust region algorithm with a nonmonotone filter technique for bound constrained optimization. The derivative-free strategy is applied for special minimization functions in which derivatives are not all available. A nonmonotone filter technique ensures not only the trust region feature but also the global convergence under reasonable assumptions. Numerical experiments demonstrate that the new algorithm is effective for bound constrained optimization. Locally, optimal parameters with respect to overall computational time on a set of test problems are identified. The performance of the best choice of parameter values obtained by the algorithm we presented which differs from traditionally used values indicates that the algorithm proposed in this paper has a certain advantage for the nondifferentiable optimization problems.