Optimasi Travelling Salesman Problem Pada Angkutan Sekolah Menggunakan Algoritme Ant Colony Optimization (Studi Kasus: MI Salafiyah Kasim Blitar) - Moh. Ibnu Assayyis; Imam Cholissodin; Tibyani Tibyani (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
Mobility is the movement from one place to another, where in the implementation of mobility requires a tool that can support. The field associated with mobility is transportation. The use of transportation is applied in MI Salafiyah Kasim as a solution to ease the burden of guardians. Because the guardian can not every day pick up their children from school, especially the age of students who are still very young and worried about having to go or go home from school alone and distance of school and home far enough. Optimization of the school's own private transportation will be expected to bring the optimal solution to minimize constraints, such as: lack of efficiency in delivery times, traffic accidents, to save the school budget. Ant Colony Optimization (ACO) is the preferred algorithm for optimizing Travelling Salesman Problem (TSP) problems. In this research, the data is the distribution of kloter delivery of students to homes divided by 2 kloter. Where the total number of students is 44 people, the first group of 20 people and the second group of 24 people. From the test results obtained best optimization was 5,711 km (22,71%) on first cluster and 34,5551 km (62,14%) on second cluster.