摘要：Choice Based Course Selection (CBCS) allows students to select courses
based on their preferred sequence. This preference in selection is normally bounded
by constraints set by a university like pre-requisite(s), minimum and maximum
number of credits registered per semester. Unplanned course sequence selection
affects the performance of the students and may prolong the time to complete the
degree. Course Difficulty Index (DI) also contributes to the decline in the
performance of the students. To overcome these difficulties, we propose a new Subset
Sum Approximation Problem (SSAP) aims to distribute courses to each semester with
approximately equal difficulty level using Maximum Prerequisite Weightage (MPW)
Algorithm, Difficulty Approximation (DA) algorithm and Adaptive Genetic Algorithm
(AGA). The three algorithms have been tested using our university academic dataset
and DA algorithm outperforms with 98% accuracy than the MPW and AGA
algorithm during course distribution.
