THE SAMPLE SCHEDULING APPLICATION OF THE ANT COLONY OPTIMIZATION ALGORITHM IN VEHICLE ROUTING PROBLEM TO FIND THE SHORTEST ROUTE
Abstract
In this collaborative research initiative with the Research Center and Industry Standardization in Surabaya, the primary objective is to obtain Indonesian National Standard certificates through the collection of samples from companies in East Java. The focal challenge revolves around the optimization of delivery routes for vehicles with specific capacities, constituting the Vehicle Routing Problem (VRP), and is addressed through the application of the Ant Colony Optimization (ACO) algorithm. The study confronts constraints, including the limitation of time and resources during the sample collection process, and grapples with challenges associated with travel distances that impact overall efficiency. The utilization of Sample Scheduling software (Si Dull) developed in Visual Basic introduces configurational constraints for route planning with the aim of minimizing distances. The overarching aim is to implement the ACO algorithm, culminating in the development of the Si Dull application, to elevate the efficacy of the sample collection process for industrial certification in Surabaya, thereby contributing to enhanced efficiency in travel distances for sample collection endeavors
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