The distribution of goods becomes a very calculated thing in the economic aspect, especially in the case of wide and complex distribution. The greater the range of distribution of goods, the more precise, fast, and accurate calculations are needed. Specifically, the calculation of the distribution required starts from mileage, total travel time, customer satisfaction level based on customer time windows, and operational costs. Vehicle Routing Problem (VRP) is a solution to the problem of distributing goods from the depot to its customers. This study aims to determine the optimal route. The methods used for VRP optimization are the Genetic Algorithm (GA) and Tabu Search (TS) methods. Fuzzy logic is used to provide leeway on the limitations of the time windows parameters, thus providing a time tolerance in the event of early arrival of the vehicle or delay in delivery. Data processing using the GA-TS combination was carried out as many as two types of trials, namely trials with the same dataset ten times and trials with various types of datasets ten times. The results of the first trial fitness value on E-VRPFTW average increased by 14.39% compared to the results of the E-VRPTW fitness value that did not use fuzzy. The results of the second trial also experienced an average increase of 8.49% compared to the results of the E-VRPTW fitness value that did not use fuzzy. Therefore, the addition of fuzzy logic has an effect in determining the optimum route of E-VRPTW.
Mobil merupakan transportasi darat yang sangat membantu aktivitas manusia dalam melakukan kegiatan seharihari. Toyota Avanza 47% mendominasi pasar mobil bekas dibanding merek lainnya. Dalam transaksi jual beli mobil bekas, selisih harga yang berbeda sering memiliki nilai yang jauh berbeda. Logika fuzzy dapat digunakan untuk memprediksi harga mobil bekas dengan memperhatikan beberapa aspek. Penelitian ini bertujuan untuk membandingkan tingkat akurasi prediksi antara metode Fuzzy Tsukamoto dengan Fuzzy Sugeno. Fuzzy Tsukamoto bersifat intuitif dan dapat memberikan tanggapan berdasarkan informasi yang bersifat kualitatif, tidak akurat, dan ambigu. Sedangkan Fuzzy Sugeno yang terdiri atas basis aturan dengan beberapa aturan penarikan kesimpulan fuzzy. Gagasan ini ditulis dengan analisis melalui studi literatur buku, jurnal dan pengumpulan data berupa dataset maupun landasan teori yang terkait. Berdasarkan analisis data sampel penjualan mobil bekas dan pembandingan 2 metode dengan variabel yang sama. Hasil dari penelitian yang telah dihitung, diperoleh bahwa metode Fuzzy Tsukamoto memiliki tingkat error sebesar 8% dan Fuzzy Sugeno sebesar 38% pada prediksi harga mobil Toyota Avanza bekas.
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