This paper introduces the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm. Evaluation on a diverse set of floating-point benchmark problems show that heuristic space diversity has a significant impact on hyper-heuristic performance. The increasing heuristic space diversity strategies performed the best out of all strategies tested. Good performance was also demonstrated with respect to another popular multi-method algorithm and the best performing constituent algorithm.
Reference:
Grobler, J, Engelbrecht, AP, Kendall, G and Yadavalli, VSS. 2014. Heuristic space diversity management in a meta-hyper-heuristic framework. In: 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 6-11 July 2014, 7pp.
Grobler, J., Engelbrecht, A., Kendall, G., & Yadavalli, V. (2014). Heuristic space diversity management in a meta-hyper-heuristic framework. IEEE. http://hdl.handle.net/10204/8222
Grobler, J, AP Engelbrecht, G Kendall, and VSS Yadavalli. "Heuristic space diversity management in a meta-hyper-heuristic framework." (2014): http://hdl.handle.net/10204/8222
Grobler J, Engelbrecht A, Kendall G, Yadavalli V, Heuristic space diversity management in a meta-hyper-heuristic framework; IEEE; 2014. http://hdl.handle.net/10204/8222 .
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