ABSTRAKSI: Differential Evolution adalah sebuah algoritma optimasi yang termasuk dalam Evolutionary Algorithms, DE menelusuri ruang solusi dengan mutasi semi terarah sehingga pada banyak kasus bernilai real, DE dapat menemukan solusi optimal dengan cepat. Resource allocation adalah sebuah permasalahan menempatkan sumber daya yang tersedia untuk memenuhi target yang ingin dicapai. Resource allocation memiliki objektif yang berbeda-beda pada setiap kasus, namun dalam menemukan solusi menggunakan DE, kasus tersebut harus dapat direpresentasikan ke dalam bentuk real.
Dalam tugas akhir ini DE diimplementasian untuk menemukan solusi dalam pengalokasian sejumlah sumber daya truk ke beberapa TPK sekaligus mendapatkan rute kunjungan setiap truk ke sejumlah TPK. Tujuannya adalah untuk memperkecil jumlah truk yang digunakan tanpa melebihi waktu maksimal operasional truk masing-masing.
Hasil pengujian menunjukkan bahwa DE dapat menemukan solusi optimum untuk studi kasus resource allocation ini, dan dapat menemukan solusi yang acceptable hanya dengan 10 generasi dengan ukuran populasi sebesar 200 dan menggunakan F sebesar 0.02, lamda 0.05, dan Pc 0.9Kata Kunci : differential evolution, resource allocation, evolutionary computation, CTSPABSTRACT: Differential Evolution is an optimization algorithm in Evolutionary Algorithm. DE finds the solution in with semi-directed mutation so it could find the optimal solution quickly in many cases. Resource allocation is a problem to allocating available resources to achieve desired goals. Resource allocation has different objectives in each case, but to find the solution using DE, we must first able to represent the problem into real format.
In this final project, has been developed a sistem using DE that able to find a solution in allocating truck resources in milk depots that have several points to be visited and each points have different time cost, loading time, and milk volume that have to be carried to depot and find the best route of each truck. The goal is to minimize the truck being used without exceed the truck's maximum operational time which is 5 hours.
In this final project, has been developed a sistem using DE that able to find a solution in allocating truck resources in milk depots that have several points to be visited and each points have different time cost, loading time, and milk volume that have to be carried to depot and find the best route of each truck. The goal is to minimize the truck being used without exceed the truck's maximum operational time which is 5 hours.In this final project, has been developed a sistem using DE that able to find a solution in allocating truck resources in milk depots that have several points to be visited and each points have different time cost, loading time, and milk volume that have to be carried to depot and find the best route of each truck. The goal is to minimize the truck being used without exceed the truck's maximum operational time which is 5 hours.Keyword: differential evolution, resource allocation, evolutionary computation, CTSP