Measuring Accuracy Score for Examination Room Scheduling Using Genetic Algorithm
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Abstract
Genetic Algorithm (GA) is a proper algorithm for solving room scheduling problems. Its output generated is conflict-free from constraints, unlike several machine learning algorithms for which constraints cannot be expressed. GA computes accuracy score of gene sequence which comply to the conflict constraints. Its disadvantage on processing time can be remedied by properly encoding chromosome that fits the computation. In this article, the metrics for measuring the accuracy score and committees’ effective time usage for seniors’ special project examination room scheduling. The output schedule by the algorithm is conflict-free such that each committee can attend the students’ presentation with no time-conflict. In particular, the output schedule satisfies the time required for the examination period. Effective time usage is defined as the total number of days required from each committee is minimized. The upper-bound and lower-bound of the schedule accuracy are calculated using the total number of days defined.
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