Optimizing Goods Delivery with Vehicle Routing Problem Time Window using the Bee Colony Algorithm

Abstract

ABSTRACT
briefly described. In this case the author lists the main findings of this research. For example, researchers found that the Bee Colony algorithm was able to provide a better solution or closer to the optimal solution in solving VRPTW. Other findings may include factors that influence algorithm performance, such as problem size and time window complexity. This research shows that the Bee Colony algorithm can be used as an effective method in solving VRPTW problems. This contributes to the development of optimal solutions in goods delivery logistics. The Bee Colony algorithm can provide a solution that minimizes the total time and distance of vehicle travel and fulfillIn this section, we will briefly explain the VRPTW problem. This problem involves delivering goods from a depot to a number of customers taking into account predetermined time constraints. Vehicles are required to organize efficient delivery schedules so that travel time is minimal and all customers are served on time. In this research, the Bee Colony algorithm is used to solve the VRPTW problem. This algorithm is inspired by the behavior of bees in searching for food. This algorithm consists of a number of worker bees that search for the best solution through iteration and an information exchange process. Through this mechanism, the Bee Colony algorithm is able to find the optimal solution or close to the optimal solution for the VRPTW problem. In this section, we will explain the implementation of the Bee Colony algorithm in solving VRPTW. By carrying out trials and experiments using datasets that are relevant to the VRPTW problem. The experimental results are s all time windows.