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AUTHOR(S):

Ismail Olaniyi Muraina, Segbenu Joseph Zosu

 

TITLE

Artificial Intelligent Rule-Based Optimization for Course Allocation Challenges

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ABSTRACT

Anytime we are crucial with time, accuracy, and error free of processing data, using machine learning tactic to handle the necessary procedures always prove encouraging and convenient than manual methods. The usual way of solving the general assignment problem by most institutions is to manually examine the full list of courses in some predefined order and for each course to find a corresponding shortlist of best-fitting lecturers, and then assign one of those lecturers to the course. This practice is simple and can be accomplished by a HOD of the department, the HOD, from his/her experience, may use search tools (Qualifications, Years of experience, area of specialization) to search for a lecturer with characteristics or criteria required by the course, to allocate courses to such lecturer. However, the procedure has the following significant drawbacks: It is tedious, repetitive, and time-consuming. Since the shortlist of matches is not prioritized within itself, it requires further manual work to rank-order the individuals in the shortlist and is thus likely to result in a suboptimal choice, even for the single course currently considered. The first course considered is likely be assigned the best-found competent lecturer for the course (a greedy policy), even though that lecturer may be better suited to other courses that have not yet been assigned. In searching for lecturers who possess a number of desired attributes, all attributes are viewed as having the same importance. When some attributes are of higher importance than others, finding the best matches must be achieved manually by first searching for lecturers with the most important attribute, then reducing the list to those also having the next important attribute, and so on. In carrying out this procedure, it is likely to lead to a serious confusion of allocation. Given the above drawbacks, the potential for large amounts of data, and the need for a short response time, an automated procedure to optimize the set of assignments could offer a significant benefit, hence the reason for solving the assignment problem would be achieved successfully. This paper looks into effectiveness involving in the allocating the teachers to the relevant courses,

KEYWORDS

Artificial Intelligence, Course Allocation, Optimization, Visirule, Assignment Problem

 

Cite this paper

Ismail Olaniyi Muraina, Segbenu Joseph Zosu. (2021) Artificial Intelligent Rule-Based Optimization for Course Allocation Challenges. International Journal of Applied Physics, 6, 42-48

 

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