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Issue title: Special Section: Computational Human Performance Modelling for Human-in-the-Loop Machine Systems
Guest editors: Hoshang Kolivand, Valentina E. Balas, Anand Paul and Varatharajan Ramachandran
Article type: Research Article
Authors: Sivaram, Murugana; * | Batri, K.b | Mohammed, Amin Salihc | Porkodi, V.d | Kousik, N.V.e
Affiliations: [a] Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam | [b] Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology | [c] Department of Computer Science Engineering, Lebanese French University, Iraq | [d] Department of Information Technology, Lebanese French University, Iraq | [e] Department of Computing Science and Engineering, Galgotias University, Greater Noida, Uttarpradesh, India
Correspondence: [*] Corresponding author. Murugan Sivaram, Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam. E-mail: sivaram.murugan@tdtu.edu.vn.
Abstract: This article explores the odd and even point crossover based Tabu Genetic Algorithm. The search optimization tools equipped with exploration and exploitation operators. Those operators assist the optimization tools for finding the optimal solution. Few problems demand vigorous exploration and minimal exploitation. The vigorous exploration needs some specialized operators, which is capable of carrying out the task. In this article, we explore one such possible operator using odd and even point (OEP) crossover. The resultant hybrid GA namely OEP crossover based Tabu GA has two tuning factors namely tenure period and OEP crossover probability (Podd). The tenure period may be a single entity or a group of entities. However, Podd is single, as the tenure period is involved with group of entities, it demands some fine tuning. The fine tuning may alter the proportion of exploration and exploitation. Hence, we proposed a method for selecting the tenure period. The proposed exploration operator and the method for fixing the tenure period has been tested over the data fusion problem in information retrieval. The results look promising.
Keywords: Tabu search, genetic algorithm, OEP crossover, Tabu GA, information retrieval, data fusion, tenure period
DOI: 10.3233/JIFS-189025
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 4, pp. 5407-5416, 2020
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