Optimization Of Vehicle Routing Problem With Time Windows VRPTW Using Hybrid Ant Colony Optimization ACO On Food Product Distribution Routes
DOI:
https://doi.org/10.33050/ccit.v19i2.4207Keywords:
Vehicle Routing Problem with Time Windows, Ant Colony Optimization, Nearest NeighborAbstract
The problem of vehicle scheduling and route optimization in food product distribution is a complex logistical challenge, especially when considering customer time window constraints and vehicle capacity. This study aims to implement a combination of Ant Colony Optimization (ACO) and Nearest Neighbor (NN) to solve the Vehicle Routing Problem with Time Windows (VRPTW) in the distribution system of HoneyBee Bakery & Cake. The Nearest Neighbor (NN) method is used to generate the initial solution, while Ant Colony Optimization (ACO) is applied to further optimize the route. The experimental results show that the Hybrid Ant Colony Optimization approach produces an initial solution with a travel distance of 72.55 km, which is then optimized to a final distance of 58.59 km with four returns to the depot. Therefore, the Hybrid ACO is proven to be more effective in optimizing distribution routes that consider both time constraints and vehicle capacity, achieving an efficiency improvement of 19.22% in reducing the total travel distance from the initial solution.
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