Load Balancing in Multi Depot Pickup and Delivery Problem with Ant Colony Optimization

The delivery services businesses are expanding as the need for these services grows. Consequently, one of the objectives is finding the carriers' shortest routes to increase the profit margins effectively. Additionally, working load balancing among carriers is considered a secondary objective of this problem to maintain employee satisfaction. The problem considers a pickup and delivery problem with multiple starting locations of the carriers due to the characteristics of non-full-time-employed drivers while also considering the limited capacity each carrier can hold. Therefore, this study proposes using Ant Colony Optimization (ACO) to balance the workload of each carrier in the Multi Depot Pickup and Delivery Problem while minimizing the total distance. This study also tested various objective functions with randomly generated 20, 50, and 100 customers to evaluate their performance. The results showed that the functions could reduce the variance of the solution and lower the overall distance. Moreover, the proposed algorithm can be used in practice.