Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search
Nonsmooth optimization through mesh adaptive direct search and variable neighborhood search
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DOI：
10.1007/s10898-007-9234-1
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发表时间：
2008-06-01
影响因子：
1.8
通讯作者：
Le Digabel, Sebastien
中科院分区：
文献类型：
--
作者：
Audet, Charles;Bechard, Vincent;Le Digabel, Sebastien
本文提出了一种联合收割机结合网格自适应直接搜索（MADS）算法和可变邻域搜索（VNS）元启发式算法求解非光滑约束优化问题的方法。由此产生的算法保留了MADS的收敛特性，并允许VNS的远距离探索功能远离局部解。本文还提出了一种通用的方法来使用代理函数的VNS搜索。数值结果说明了该方法的优点和局限性。
This paper proposes a way to combine the Mesh Adaptive Direct Search (MADS) algorithm, which extends the Generalized Pattern Search (GPS) algorithm, with the Variable Neighborhood Search (VNS) metaheuristic, for nonsmooth constrained optimization. The resulting algorithm retains the convergence properties of MADS, and allows the far reaching exploration features of VNS to move away from local solutions. The paper also proposes a generic way to use surrogate functions in the VNS search. Numerical results illustrate advantages and limitations of this method.