Abstract:
Route optimization is a common challenge in the field of transportation. This research
aims to optimize pickup passenger routes using a genetic algorithm and Geographical
Information System for travel purposes. The primary objective is to minimize the total
distance and travel time for passengers. The genetic algorithm is utilized to generate
potential route populations, where each route represents a feasible pickup sequence. By
applying crossover and mutation operators, the algorithm explores the solution space to
find near-optimal routes. Fitness evaluation takes into account various factors,
including distance and travel time, resulting in efficient and comfortable routes for
passengers. To validate the proposed approach, real-world sample data of pickup
passengers from CV. Gabus Rawa Travel is used. The results highlight the effectiveness
of the genetic algorithm in optimizing pickup passenger routes. This approach enables
transportation service providers to improve resource allocation, reduce travel time and
distance traveled for pickup passengers. The system generated is efficient in producing
optimal routes with a time complexity of O(n^3), thus enhancing the efficiency of the
pickup passenger travel process.
