Pengaruh Hybrid Adaptive Repairing Genetic Algorithm dan VIKOR-Based Fitness dalam Optimasi Penjadwalan Perkuliahan

Eka Yulia Sari; Titik Rahmawati; Agung Priyanto

doi:10.55338/jumin.v7i1.7676

Authors

Eka Yulia Sari, Universitas Sarjanawiyata Tamansiswa, Indonesia
Titik Rahmawati, Universitas Sarjanawiyata Tamansiswa, Indonesia
Agung Priyanto, Universitas Sarjanawiyata Tamansiswa, Indonesia

DOI:

https://doi.org/10.55338/jumin.v7i1.7676

Keywords:

Algoritma Hybrid Genetika, Hybrid Adaptif Repairing, Vikor-Based Fitness, Optimasi Penjadwalan, Multi-Criteria Decision Making (MCDM)

Abstract

Permasalahan penjadwalan perkuliahan merupakan masalah optimasi multi-kriteria yang kompleks karena melibatkan berbagai constraint yang saling berkonflik. Penelitian ini mengusulkan penerapan Hybrid Adaptive Repairing Genetic Algorithm (HAR-GA) yang dikombinasikan dengan VIKOR-based fitness untuk meningkatkan kualitas solusi penjadwalan. Mekanisme adaptive repairing digunakan untuk memperbaiki solusi infeasible secara eksplisit selama proses evolusi, sedangkan VIKOR diterapkan sebagai fungsi fitness untuk menyeimbangkan pelanggaran antar kriteria constraint. Evaluasi dilakukan dengan membandingkan HAR-GA terhadap algoritma genetika tanpa mekanisme repair serta HAR-GA dengan fitness standar. Hasil eksperimen menunjukkan bahwa HAR-GA mampu menghasilkan solusi feasible dengan best violation = 0 pada generasi ke-162, sementara algoritma genetika tanpa repairing masih menghasilkan rata-rata minimum violation sebesar 252,16. Selain itu, HAR-GA menurunkan rata-rata minimum violation menjadi 52,82 dan rata-rata maksimum violation menjadi 105,28. Integrasi VIKOR-based fitness memberikan peningkatan kinerja lebih lanjut dengan menurunkan rata-rata minimum violation sebesar 38,8%, rata-rata mean violation sebesar 33,5%, serta standar deviasi sebesar 45,6% dibandingkan fitness standar. Hasil ini menunjukkan bahwa kombinasi HAR-GA dan VIKOR-based fitness efektif dalam meningkatkan kualitas, stabilitas, dan keseimbangan solusi pada permasalahan optimasi penjadwalan multi-kriteria.

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