Optimization of Obsolescence Forecasting Using New Hybrid Approach Based on the RF Method and the Meta-heuristic Genetic Algorithm

Grichi,Yosra; Beauregard,Yvan; Dao,Thien-My

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AMERICAN JOURNAL OF MANAGEMENT

Optimization of Obsolescence Forecasting Using New Hybrid Approach Based on the RF Method

and the Meta-heuristic Genetic Algorithm

Author(s): Yosra Grichi, Yvan Beauregard, Thien-My Dao

Citation: Yosra Grichi, Yvan Beauregard, Thien-My Dao, (2018)"Optimization of Obsolescence Forecasting Using New Hybrid Approach Based on the RF Method and the Meta-heuristic Genetic Algorithm ," American Journal of Management, Vol. 18, Iss. 2, pp. 27-38

Article Type: Research paper

Publisher: North American Business Press

Abstract:

Obsolescence is highly complex problems due to the influence of many factors such as technological

advancement. However, prediction of obsolescence appears to be one of the most efficient solutions. This paper proposes a novel approach known as GA-RF for obsolescence forecasting. Genetic algorithm (GA) searches for optimal parameters and feature selection to construct a random forest (RF) in order to improve the classification of RF. To examine the feasibility of this approach, this paper presents a comparison between GA-RF, RF, Stepwise logistic regression, and stochastic gradient boosting. Experimental results show that GA-RF outperformed the other methods with 93.3% of accuracy, 90.4% of sensitivity and 95.4% of specificity.