# Iterated local search

> kind of metaheuristic algorithm

**Wikidata**: [Q6094397](https://www.wikidata.org/wiki/Q6094397)  
**Wikipedia**: [English](https://en.wikipedia.org/wiki/Iterated_local_search)  
**Source**: https://4ort.xyz/entity/iterated-local-search

## Summary
Iterated local search is a type of metaheuristic algorithm that enhances the performance of local search methods by repeatedly applying them with modifications to escape local optima and improve solution quality. It is a subclass of metaheuristic algorithms, which are higher-level procedures designed to find, generate, or select heuristics.

## Key Facts
- Subclass of metaheuristic algorithms
- Designed to improve local search performance by iterative refinement
- Helps escape local optima through repeated application
- Freebase ID: /m/0g59x6r
- Wikipedia title: Iterated local search
- Available in Wikipedia languages: Bulgarian, Catalan, English, Italian
- Wikidata description: "kind of metaheuristic algorithm"
- Microsoft Academic ID (discontinued): 124145224
- Sitelink count: 4

## FAQs
### Q: What is the primary purpose of iterated local search?
A: Iterated local search aims to enhance the performance of local search methods by repeatedly applying them with modifications to escape local optima and improve solution quality.

### Q: How does iterated local search differ from other metaheuristic algorithms?
A: Unlike some metaheuristic algorithms, iterated local search specifically focuses on iterative refinement and modification of local search methods to achieve better results.

### Q: In which fields is iterated local search commonly used?
A: Iterated local search is applied in optimization problems where local search methods are used, such as combinatorial optimization and machine learning.

## Why It Matters
Iterated local search plays a crucial role in optimization problems by improving the efficiency and effectiveness of local search methods. By iteratively applying and modifying local search techniques, it helps escape local optima, leading to better solutions. This makes it valuable in fields such as combinatorial optimization, machine learning, and operations research. Its ability to enhance local search performance makes it a significant tool in metaheuristic optimization.

## Notable For
- Being a subclass of metaheuristic algorithms
- Enhancing local search performance through iterative refinement
- Helping escape local optima in optimization problems
- Available in multiple Wikipedia languages
- Having a Wikidata entry with a specific description

## Body
### Classification
Iterated local search is classified as a metaheuristic algorithm, which is a higher-level procedure designed to find, generate, or select heuristics. It is a specific type of metaheuristic that focuses on improving local search methods through iteration.

### Usage
The algorithm is commonly used in optimization problems where local search methods are applied. It helps in escaping local optima by repeatedly applying and modifying local search techniques, leading to better solutions.

### Availability
Iterated local search has Wikipedia entries in Bulgarian, Catalan, English, and Italian. It also has a Wikidata entry with a specific description and a sitelink count of 4.

### Identification
The algorithm can be identified by its Freebase ID (/m/0g59x6r) and Microsoft Academic ID (124145224). Its Wikipedia title is "Iterated local search," and it is part of the metaheuristic class of algorithms.

## References

1. [OpenAlex](https://docs.openalex.org/download-snapshot/snapshot-data-format)