A Derivative-Free Optimization Algorithm Using Sparse Grid Integration

• 作者: Shengyuan Chen Xiaogang Wang
• 来源期刊: 美国计算数学期刊(英文)
• 学科: 数学
• 关键词: Nonlinear Programming Derivative Free Optimization SPARSE Grid Numerical INTEGRATION CONDITIONAL MOMENT
• 年，卷（期）: 2013,（1）
• 页码范围: 16-26
• 页数: 11页
• 分类号: O1

摘要

We present a new derivative-free optimization algorithm based on the sparse grid numerical integration. The algorithm applies to a smooth nonlinear objective function where calculating its gradient is impossible and evaluating its value is also very expensive. The new algorithm has: 1) a unique starting point strategy;2) an effective global search heuristic;and 3) consistent local convergence. These are achieved through a uniform use of sparse grid numerical integration. Numerical experiment result indicates that the algorithm is accurate and efficient, and benchmarks favourably against several state-of-art derivative free algorithms.