In this chapter, I only consider those approaches that accept an improving solution that can be generated from one iteration to the next. Basic neighbourhood definitions with simple examples are first provided. This is followed by the descent or greedy method while emphasising some of its drawbacks. I then present some of the efficient hill climbing methods commonly used such as GRASP, a simple composite heuristic, multi-level, variable neighbourhood and perturbation schemes. A brief on large neighbourhood search, iterated local search and guided local search will also be given.
KeywordsImprovement only heuristics Hill climbing GRASP VNS Multi-level Perturbation
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