Judul: Solving the Capacitated Vehicle Routing Problem Using the Particle Swarm Optimization Algorithm
Abstrak: Capacitated vehicle routing problem (CVRP) merupakan salah satu permasalahan pendistribusian yang memperhatikan kendala kapasitas kendaraan. Ada beberapa metode yang dapat digunakan untuk menyelesaikan permasalahan ini. Pada karya ilmiah ini, digunakan metode meta-heuristic Particle Swarm Optimization (PSO) dengan bantuan algoritme Sweep. Pada tahap pertama algoritme sweep digunakan untuk pembentukan grup dari sejumlah pelanggan berdasarkan urutan sudut polar setiap posisi pelanggan terhadap depot. Selanjutnya algoritme PSO digunakan dalam penentuan rute pendistribusian di setiap grup. Diawali dengan inisialisasi parameter yang digunakan. Kemudian membangkitkan kecepatan dan posisi awal secara acak. Tahap selanjutnya menghitung nilai fungsi tujuan serta yang terakhir menentukan P_best (posisi terbaik dari suatu partikel) dan G_best (posisi terbaik dari seluruh partikel). Aplikasi permasalahan CVRP pada karya ilmiah ialah penentuan rute pendistribusian roti dengan meminimumkan jarak tempuh., Capacitated vehicle routing problem (CVRP) is one of the distribution problem that takes into account vehicle capacity constraints. There are several methods that can be used to solve this problem. In this research, the meta-heuristic Particle Swarm Optimization (PSO) method is used with Sweep algorithm. In the first step, the sweep algorithm is used to form a group from a number of customers based on the polar angle order of each customer position towards the depot. Furthermore, the PSO algorithm is used in determining of distribution routes in each other. Starting with the initialization of the parameter used. Then increase the speed and starting position randomly. Next stage is to calculate the objective function value and the last is measuring P_best (best position of a particle) and G_best (best position of all particles). The application of CVRP problems in this research is determining of route distribution of the bread by minimizing the mileage.
Keyword: CVRP, meta-heuristic, particle swarm optimization, sweep algorithm

Judul: Determination of Capacitated Vehicle Routing  Problem Using Ant Colony Optimization and Simulated Annealing
Abstrak: Capacitated Vehicle Routing Problem (CVRP) merupakan variasi dari Vehicle Routing Problem (VRP). CVRP bertujuan mencari rute yang meminimalkan biaya transportasi untuk melayani semua pelanggan dengan tetap memperhatikan kendala kapasitas kendaraan. CVRP bersifat NP-Hard problem sehingga sulit menyelesaikan masalah ini secara langsung. Terdapat beberapa metode metaheuristic yang dapat digunakan untuk menyelesaikan permasalahan ini. Pada karya ilmiah ini, metode metaheuristic yang digunakan untuk menyelesaikan CVRP adalah metode Ant Colony Optimization (ACO) dan metode Simulated Annealing (SA). Penelitian ini menggunakan tujuh kasus CVRP. Hasil penelitian memperlihatkan bahwa waktu eksekusi metode SA relatif lebih cepat untuk kasus dengan jumlah node yang sedikit, tetapi relatif lebih lama untuk jumlah node yang lebih banyak dibandingkan metode ACO. Selain itu, total jarak yang dihasilkan metode SA lebih optimal dibandingkan total jarak yang dihasilkan metode ACO., Capacitated Vehicle Routing Problem (CVRP) is a variation of the Vehicle Routing Problem (VRP). CVRP aims to find routes that minimize transportation costs to serve all customers while taking into account vehicle capacity constraints. CVRP is an NP-Hard problem so it is difficult to solve this problem directly. There are several metaheuristic methods that can be used to solve this problem. In this scientific work, the metaheuristic methods used to solve CVRP are the Ant Colony Optimization (ACO) method and the Simulated Annealing (SA) method. This research uses seven CVRP cases. The results show that the execution time of the SA method is relatively faster for cases with a small number of nodes, but relatively longer for a larger number of nodes than the ACO method. In addition, the total distance generated by the SA method is more optimal than the total distance generated by the ACO method.
Keyword: Ant Colony Optimization, Capacitated Vehicle Routing Problem, metaheuristic, Simulated Annealing

Judul: Profil Antibodi IgM dan IgG pada Beruk (Macaca nemestrina) setelah Diinfeksi Virus Dengue Serotipe-3 (DEN-3) melalui Rute Intravena
Abstrak: The aim of this study was to detect IgM and IgG in pig-tailed macaques (Macaca nemestrina) primarily innoculated by Dengue virus serotype-3 (DEN-3) by intravenous route. A total of 84 plasma samples were examined in the study. Plasma samples were taken on day 0 before infection, followed by plasma collections on day 1 through day 13 post infection. The obtained plasma samples were analyzed using indirect ELISA test. The results showed the increasing titer of IgM started on day-3 post infection with its peak occurred on day 11 post infection and started to decline afterward; while the IgG titer started to increase on day 6 or day 7 post infection and continue to increase until the day 13 post infection. These results showed that in a primary infection of DEN-3 byintravenous route, the tendency of IgM titer increase was higher than the IgG titer increase; also shown that the IgM titer increase was occured earlier than IgG. The profile of IgM and IgG antibodies is outlined in this study.
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