Guided Local Search

Abstract

Abstract Guided local search (GLS) is a metaheuristic method proposed to solve combinatorial optimization problems. It is a high‐level strategy that applies an efficient penalty‐based approach to interact with the local improvement procedure. This interaction creates a process capable of escaping from local minima, which improves the efficiency and robustness of the underlying local search algorithms. Fast local search (FLS) is a local search algorithm, which improves the efficiency of local search by reducing the size of the neighborhood. GLS can be efficiently combined with FLS in the form of guided fast local search (GFLS). This article describes the principles of GLS, FLS, and GFLS. It also surveys GLS's extensions, hybrids, and applications.