<![CDATA[The development of the modern retail industry has increased goods distribution activities, creating a need for efficient and environmentally friendly distribution systems. This study aims to optimize distribution routes at the Gorontalo Alfamart Distribution Depot using the Green Vehicle Routing Problem with Time Windows (G-VRPTW) model by considering vehicle capacity, service time windows, load-dependent fuel consumption, and vehicle carbon emissions. The model is solved using a Genetic Algorithm as a metaheuristic method. The solution is represented using permutation encoding, with optimization stages consisting of initial population generation, selection, crossover, mutation, and fitness evaluation. The research data were obtained from the distribution system of the Gorontalo Alfamart Distribution Depot. The optimization results show that the Genetic Algorithm produces more efficient routes than the company's actual routes. The total travel distance was reduced from 1,075.24 km to 774.69 km, representing a reduction of 27.95%, while fuel consumption decreased from 65.124 L to 45.4573 L, representing a reduction of 30.20%. Accordingly, estimated carbon emissions decreased from 165.413 kg CO₂ to 115.4619 kg CO₂, representing a reduction of 30.20%. These results indicate that the developed G-VRPTW model based on the Genetic Algorithm can support the implementation of green logistics by improving distribution efficiency and reducing environmental impacts.]]>
Copyrights © 2026
