Variable neighborhood search: basics and variants

Variable neighborhood search (VNS) is a framework for building heuristics, based upon systematic changes of neighborhoods both in a descent phase, to find a local minimum, and in a perturbation phase to escape from the corresponding valley. In this paper, we present some of VNS basic schemes as well as several VNS variants deduced from these basic schemes. In addition, the paper includes parallel implementations and hybrids with other metaheuristics.

变邻域搜索（VNS）是一种构建启发式算法的框架，它基于在下降阶段（以找到局部最小值）和扰动阶段（以逃离相应的山谷）对邻域进行系统性改变。在本文中，我们介绍了一些VNS基本方案以及从这些基本方案推导出来的几种VNS变体。此外，本文还包括并行实现以及与其他元启发式算法的混合。