Hybrid Genetic Algorithms: A Review
2006
Hybrid genetic algorithms have received significant interest in recent years and are being increasingly used to solve real-world problems. A genetic algorithm is able to incorporate other techniques within its framework to produce a hybrid that reaps the best from the combination. In this paper, different forms of integration between genetic algorithms and other search and optimization techniques are reviewed. This paper also aims to examine several issues that need to be taken into consideration when designing a hybrid genetic algorithm that uses another search method as a local search tool. These issues include the different approaches for employing local search information and various mechanisms for achieving a balance between a global genetic algorithm and a local search method. Index Terms—Genetic algorithms, evolutionary computation, hybrid genetic algorithms, genetic-local hybrid algorithms, memetic algorithms, Lamarckian search, Baldwinian search.
Keywords:
- Incremental heuristic search
- Machine learning
- Cultural algorithm
- Artificial intelligence
- Population-based incremental learning
- Beam search
- Genetic representation
- Meta-optimization
- Computer science
- Quality control and genetic algorithms
- Memetic algorithm
- Guided Local Search
- Local search (optimization)
- Metaheuristic
- Correction
- Source
- Cite
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