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Automated University Lecture Schedule Generator based on Evolutionary Algorithm yusri ikhwani; Khairan Marzuki; As’ary Ramadhan
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 22 No. 1 (2022)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2215

Abstract

university is a complicated work so in the implementation it have violation of the constraints and it also takes a lot of time since it is created manually. In this paper evolutionary algorithm (EA) is used to create an effective and feasible schedules based on the real data input that is obtained from each department. The objective functions in EA contribute in gaining the fitness function to solve the constraints problem in the schedule by applying weighting for each hard constraints. The objective function is gained from the total of infringement in each soft constraints addition by score weighting. The genetic operator used in EA is stochastic variation Operator. As far as the reproduction operator is concerned, the tournament selection was used with size 3. Crossover operator is conducted after selection process with crossover probability equal to 0.05 and mutation rate is 0.1. The size of population was set to 9 and stopping criteria algorithm was left run for fitness value = 1. The simulation result shows that EA can create lecture schedules efficiently and feasibly. Moreover, it is also faster with the execution time of the proposed EA is less than 30 and easier than creating manually.
Single elimination tournament design using dynamic programming algorithm yusri ikhwani; As`ary Ramadhan; Muhammad Bahit; Taufik Hidayat Faesal
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 1 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i1.3290

Abstract

Finding the best single-elimination tournament design is important in scientific inquiry because it can have major financial implications for event organizers and participants. This research aims to create an optimal single-elimination tournament design using binary tree modeling with dummy techniques. Dynamic programming algorithms have been used to compute optimal single-elimination designs to overcome this effectively. This research method uses various implementations of sub-optimal algorithms and then compares their performance in terms of runtime and optimality as a solution to measure the comparison of sub-algorithms. This research shows that the difference in relative costs produced by various sub-algorithms with the same input is quite low. This is expected because quotes are generated as integer values from a small interval 1, ≤ 9, whereas costs tend to reach much higher values. From the comparison of these sub-algorithms, the best results among the sub-optimal algorithms were obtained in the Sub Optimal algorithm 3. We present the experimental findings achieved using the Python implementation of the suggested algorithm, with a focus on the best single-elimination tournament design solution.