Implementing flower multi-objective algorithm for selection of university academic credits - Ochoa, Alberto; Gonzalez, Saul; Margain, Lourdes; Padilla, Teresa; Castillo, Oscar; Melin, Patricia (2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014), 2014)
There are several factors that can influence the selection of electives in order to complete the set of credits of a course in Bachelor level. Even though this problem has been studied repeatedly by many researchers on literature, the results have not established optimal values using bio-inspired algorithms to analyze the cost-benefit for every student in a minority group, and comparing their choices of electives according to the group. For our research, we analyzed four scholar courses with approximately 87 educational studies, this sample is composed by: Sociology, Interior Design, Sports Training & Aeronautics and we propose to use a novel nature-inspired algorithm called "Flower Pollination Algorithm," which has proven effectiveness for the cohesion of behavior associated with several problems. When we use restrictions, strategies are generated 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 to reduce the duration of the professional studies to set appropriate conditions for the selection of specialized subjects.