A Framework of Investigating the Impact of Different Data Densities on the Rates of the Genetic Operators in the Matrix-based EAs Model

摘要

This paper intends to investigate the relationship between the data density and the search operator rates in the examination room assignment problem. For this, we have suggested the Matrix-based EAs Model to solve the examination room assignment problem. In this particular problem, we allocate examinations into a number of rooms for a particular slot. Thus, data density in this paper refers to the total number of candidates for all the examinations divided by the maximum capacity of all available rooms in a particular slot. We believe that for better performance, the probability values of search operators need to be adjusted inline with different data densities.