Multiple Depot

Multiple depot problems address the optimization of logistics operations involving multiple starting points for delivery or service, aiming to minimize costs (e.g., travel distance, labor) while meeting constraints like delivery deadlines and vehicle capacity. Current research focuses on developing and refining algorithms, such as genetic algorithms, simulated annealing, and integer linear programming, to solve these complex optimization problems, often incorporating features like dynamic routing and heterogeneous fleets. These advancements have significant implications for improving efficiency and reducing costs in various sectors, including last-mile delivery, warehouse management, and field service operations.