A Genetic Algorithm for Split Delivery Open Vehicle Routing Problem with Physical Workload Consideration

Last-mile delivery is an important part of a logistics activity in the city. Usually, delivery workers are required to manually unload goods at customer locations. These manual tasks induce physiological fatigue in the workers and increase delivery time. This paper discusses a genetic algorithm (GA) approach to the open vehicle routing problem with split delivery (SDOVRP), where manual unloading is addressed. The workers are pre-assigned to vehicle and split delivery is allowed. Its objective is to minimize the total cost of total fixed cost of vehicles and delivery workers and total transportation cost. For safety, the total physical workload imposed on each worker must not exceed the daily limit. Since an optimization approach cannot find the optimal solution within reasonable computation time especially when solving large size problem. A GA with heuristic for pre-determine split delivery is developed to solve the problem. The computational experiment results show that the GA approach is efficient and can obtain near-optimal SDOVRP solutions.