Moreno-Saavedra, Luis Miguel
[VerfasserIn];
Jiménez-Fernández, Silvia
[VerfasserIn];
Portilla-Figueras, José Antonio
[VerfasserIn];
Casillas-Perez, David
[VerfasserIn];
Salcedo-Sanz, Sancho
[VerfasserIn]
A Multi-Algorithm Approach for Operational Human Resources Workload Balancing in a Last Mile Urban Delivery System
Beschreibung:
Efficient workload assignment to the workforce is critical in last-mile package delivery systems. The explosive increase in e-commerce and last-mile package logistics after the COVID-19 pandemic has led to difficulties in balancing the daily workload of the workforce in many delivery zones. Traditional methods of assigning packages to workers based on geographical proximity can be inefficient, and surely lead to an unbalanced distribution of work among delivery workers. We consider here a problem of operational human resources workload balancing in last-mile urban package delivery systems, mainly taking into account the effort workload, i.e. related to the delivery time and mainly affecting the workers' health. Specifically, we propose a multi-algorithm approach for optimizing daily human resources workload balancing in package delivery systems. The proposed approach takes as input a set of delivery points and a defined number of workers and assigns packages to workers in a way that ensures that each worker completes a similar amount of work. The proposed algorithms use a combination of distance and workload considerations to optimize the allocation of packages to workers. The distance between delivery points and the location of each worker is also taken into account to minimize the travel time, and the workload of each delivery point is considered to ensure that each worker completes a similar amount of work per day. The proposed multi-algorithm approach includes different versions of k-means, evolutionary approaches, recursive assignments based on k-means initialization with different problem encodings, and a hybrid evolutionary ensemble algorithm. We have successfully illustrated the performance of the proposed approach in a real problem of human resource balancing in an urban last-mile package delivery workforce operating at Azuqueca de Henares, Guadalajara, Spain