A Taxonomy of Hybrid Metaheuristics

By El-Ghazali Talbi. J. Heuristics, 2002

944 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/66f23d35996c5f7789c09846572ad746d998597d

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Citations in the corpus

Hybrid Genetic Algorithms: A Review (2006, background): “However, the reader can refer to [18] for an architectural taxonomy of combinatorial memetic algorithms (MA) [19] and to [20], where meta-heuristics are classified based on the design space and implantation space aspects.”
Parallelism and evolutionary algorithms (2002, methodology): “Several other heuristics such as simulated annealing [74], tabu search [48], and their combinations and variations [123] have been used with comparable results but will not be reviewed here.”
A tutorial for competent memetic algorithms: model, taxonomy, and design issues (2005, methodology): “Our taxonomy complements the taxonomies in [91] and [92].”
ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics (2004, background): “In Talbi (2002) , E.-G. Talbi has distinguished two levels and two modes of hybridization (figure 3): Low and High levels, and Relay and Cooperative modes.”
Metaheuristics in Combinatorial Optimization (2005, methodology): “Hybrids. Hybrids are aimed at exploiting the strengths of different methods by either designing a new metaheuristic that combines various algorithmic principles of the original methods or by developing multi-agent architectures in which the individual agents run pure methods and communicate among th”
Computational Finance (2014, neutral): “Talbi in (Talbi 2002) has compiled an almost exhaustive taxonomy of hybrid heuristics, which the reader may consult as a guide for mixing heuristics according to the problem at hand.”