Capacitated Vehicle Routing Problem

Capacitated Vehicle Routing Problem adalah salah satu permasalahan untuk menentukan rute optimal dimana setiap kendaraan dibatasi dengan kapasitas tertentu. Tujuan dari CVRP adalah untuk menetukan rute distribusi suatu barang yang efisien sehingga menghasilkan jarak tempuh terpendek dengan biaya minimum. Beberapa algoritma yang telah dilakukan sebagai alternatif penyelesaian masalah CVRP diantaranya adalah Ant Colony Optimization (ACO) dan Particle Swarm Optimization (PSO). Algoritma Ant Colony Optimization (ACO) merupakan algoritma yang konsep kerjanya terinspirasi dari perilaku koloni semut dalam mencari makanan dengan menemukan jarak terpendek yang diperoleh dari jejak-jejak feromon. Sedangkan algoritma Particle Swarm Optimization (PSO) terinspirasi dari perilaku sosial kolektif dari kecerdasan koloni binatang, seperti burung dan ikan. Pada penulisan ini, penulis menerapkan dua algoritma tersebut untuk mencari algoritma manakah yang lebih efisien digunakan dalam penyelesaian CVRP.

Results (English) 1:

Capacitated Vehicle Routing Problem is one of the problems to determine the optimal route where every vehicle is limited by capacity. The purpose of CVRP is to determine the route of the efficient distribution of an item so that it generates the shortest mileage with minimum cost. Several algorithms have been made as an alternative to solving problems such as CVRP Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Algorithm of Ant Colony Optimization (ACO) is the concept of algorithm works inspired by the behavior of ant colonies in search of food by finding the shortest distance is obtained from traces of pheromones. While the algorithm of Particle Swarm Optimization (PSO) is inspired from the social behavior of the collective intelligence of a colony of animals, such as birds and fish. At this writing, the authors apply the two algorithms for finding algorithm which is used in more efficient completion of CVRP.

Results (English) 2:

Capacitated Vehicle Routing Problem is one of the problems for determining the optimal route where each vehicle is limited to a certain capacity. The purpose of the CVRP is to determine the efficient distribution of goods so as to produce the shortest travel distance with minimum cost. Several algorithms have been done as an alternative to the settlement of the problem CVRP including the Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Algorithm Ant Colony Optimization (ACO) algorithm is the concept works inspired by the behavior of ant colonies in search of food by finding the shortest distance obtained from the traces of pheromones. While the algorithm Particle Swarm Optimization (PSO) was inspired by the social behavior of the collective intelligence of a colony of animals, such as birds and fish. In this paper, the authors apply these two algorithms to search for algorithms which are more efficiently used in the completion CVRP.