Shipwrecked on Fear: Selection of Electives in School Minorities in a University Using Cuckoo Search Algorithm
The purpose of this research is to understand from a Multivariable optimization related with four scholar minorities studies in a University with approximately 87 educational studies on Bachelor level, this sample is composed by: (Safety Sciences, Interior Design, Sports Training and Aeronautics) assuming that any student want to analyze the way in which these minority groups selected electives to complete the set of credits in their respective studies to determine the optimal selection which involve the choice of these materials in educational majority groups to determine the benefit-cost associated with the term professional studies, whose main base the restriction on a small number of subjects in their studies this because such a low minority enrollment, even though this problem has been studied repeatedly by many researchers on the literature have not been established optimal values by supporting bio-inspired algorithms to interact with the different values associated with the achievement of the term loans and the cost-benefit every student to a minority group and comparing their choices of electives with respect the group. There are several factors that can influence the selection of an elective, for our research we propose to use a new bio-inspired algorithm called “Cuckoo search algorithm,” which has proven effective for the cohesion of behavior associated with several problems, and when and use restrictions have strategies to keep tempo in the selection of these materials, in our case, a resource such as time gain regarding the subjects studied is represented as the optimal way for the duration of the professional studies with uncertainty not know how long it can last set appropriate conditions for the selection of specialized subjects.
KeywordsMultiobjective problem Cuckoo search algorithm and intelligent optimization
The authors were supported with funds from Social Research Center in Juarez City University and used data from Scholar Services associated with four Academic minorities in UACJ at Chihuahua State whom permits compare the simulation with real selection of subjects realized by these minorities.
- 1.Barbucha, Dariusz: Experimental study of the population parameters settings in cooperative multi-agent system solving instances of the VRP. Trans. Comput. Collective Intell. 9, 1–28 (2013)Google Scholar
- 2.Andreu R.A.: Estudio del desarrollo de aplicaciones RA para Android. Trabajo de fin de Carrera. Catalunya, España (2011)Google Scholar
- 4.Flake, G.: The Computational Beauty of Nature: Computer Explorations of Fractals, Chaos, Complex Systems, and Adaptation. MIT Press, Cambridge (1999)Google Scholar
- 5.Kitchell, A., et al.: 10 smell myths: Uncovering the sinkin’truth. Technical report, Department of Biological Sciences, University of South Carolina (1995)Google Scholar
- 6.Mendoza, R.: Involving cuckoo birds from Kandor in a Karumi representation. In: Karumi Handbook (1995)Google Scholar
- 8.Reyes, L.C., Zezzatti, O.A., et al.: A Cultural Algorithm for the Urban Public Transportation. In: HAIS, pp. 135–142 (2010)Google Scholar
- 9.Minsky, M.: The society of mind. Simon & Schuster, New York (1985)Google Scholar
- 11.Rosenblatt, J.K., et al.: A fine-grained alternative to the subsumption architecture for mobile robot control. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks (Washington DC), vol. 2, pp. 317–324, June 1989Google Scholar
- 12.Velásquez J.: Modelling emotions and other motivations in synthetic agents. In: Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97) (Providence, RI), MIT/AAAI Press (1997)Google Scholar