PENINGKATAN OPTIMASI RUTE KENDARAAN: KOMBINASI ALGORITMA GENETIKA DENGAN PENDEKATAN FIXED RADIUS NEAR NEIGHBOR

Nur Iksan, Ismail Yusuf Panessai, Pamor Gunoto, Anton Viantika, Hidayah Novitasari

Abstract


Artikel ini menyelidiki optimasi Vehicle Routing Problem menggunakan dua pendekatan berbeda: Genetic Algorithm (GA) dan Fixed Radius Near Neighbour-Genetic Algorithm (FRNN-GA). Masalah yang dihadapi melibatkan optimalisasi kendaraan multi-depot, heterogen, dan Vehicle Routing Problem (VRP) asimetris, yang merupakan tugas penting dalam logistik dan manajemen operasi. Studi ini mengevaluasi kinerja kedua algoritma dengan menganalisis nilai yang diperoleh dari generasi ke generasi dan membandingkan kualitas solusinya dalam hal pengurangan konsumsi bahan bakar. Hasilnya menunjukkan bahwa GA hibrid secara konsisten mengungguli GA umum, mencapai nilai fungsi tujuan yang jauh lebih rendah dan menunjukkan konvergensi yang lebih efisien terhadap solusi kompetitif. Temuan ini menggarisbawahi efektivitas hibridisasi algoritma genetika dengan Fixed Radius Near Neighbor (FRNN) dalam meningkatkan kualitas solusi dan efisiensi konvergensi. Studi ini memberikan kontribusi wawasan berharga ke dalam metodologi optimasi dan memberikan landasan untuk penelitian lebih lanjut dalam desain dan penerapan algoritma.

Keywords


Optimization; Rich VRP; Heuristic

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DOI: https://doi.org/10.33373/dms.v11i3.6168

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