论文信息 - Evolving heuristics with genetic programming

Evolving heuristics with genetic programming

Hyper-Heuristics are methods to choose and combine heuristics to generate new ones. In this work, we use a grammar-based genetic programming system as a Hyper-Heuristic framework. The framework is used for evolving effective incremental solvers for SAT (Inc*). Tests against well-known local search heuristics on a variety of benchmark problems reveal that the evolved heuristics are superior.

Riccardo Poli | Mohamed Bahy Bader-El-Den

[1] Riccardo Poli,et al. A Field Guide to Genetic Programming , 2008 .

[2] Graham Kendall,et al. Hyper-Heuristics: An Emerging Direction in Modern Search Technology , 2003, Handbook of Metaheuristics.

[3] Riccardo Poli,et al. Inc*: An Incremental Approach for Improving Local Search Heuristics , 2008, EvoCOP.

[4] Hector J. Levesque,et al. A New Method for Solving Hard Satisfiability Problems , 1992, AAAI.

[5] Riccardo Poli,et al. Generating SAT Local-Search Heuristics Using a GP Hyper-Heuristic Framework , 2007, Artificial Evolution.

[6] Riccardo Poli,et al. A GP-based hyper-heuristic framework for evolving 3-SAT heuristics , 2007, GECCO '07.