Procedia Computer Science
Though metaheuristics have been frequently employed to improve the performance of data mining algorithms, the opposite is not true. This paper discusses the process of employing a data mining algorithm to improve the performance of a metaheuristic algorithm. The targeted algorithms to be hybridized are the Meta-heuristic for Randomized Priority Search (Meta-RaPS) and an algorithm used to create an Inductive Decision Tree. This hybridization focuses on using a decision tree to perform on-line tuning of the parameters in Meta-RaPS. The process makes use of the information collected during the iterative construction and improvement phases Meta-RaPS performs. The data mining algorithm is used to find a favorable parameter using the knowledge gained from previous Meta-RaPS iterations. This knowledge is then used in future Meta-RaPS iterations. The proposed concept is applied to benchmark instances of the Vehicle Routing Problem. 2014 The Authors.
Original Publication Citation
Al-Duoli, F., & Rabadi, G. (2014). Data mining based hybridization of meta-RaPS. Procedia Computer Science, 36, 301-307. doi:10.1016/j.procs.2014.09.097
Al-Duoli, Fatemah and Rabadi, Ghaith, "Data Mining Based Hybridization of Meta-RaPS" (2014). Engineering Management & Systems Engineering Faculty Publications. 9.