# Introduction The operational human resources workload balancing is critical in the last mile delivery system. The traditional assignment methods of packages to workers based on geographical proximity can be inefficient and lead to an uneven distribution of workload among workers. # Problem The operational human resources workload balancing in the last mile delivery system is a complex problem that requires optimizing package assignments to workers. An uneven distribution of workload can lead to problems such as fatigue, dehydration, and injuries among workers. # Approach The multi-algorithm approach proposed uses a combination of distance and workload considerations to optimize package assignment to workers. The proposal includes various versions of k-means, evolutionary approaches, recursive assignments based on k-means initialization with different problem coding schemes, and hybrid evolutionary algorithms. # Example The proposal has been applied to a last mile delivery system operating in Azuqueca de Henares, Spain. The results have shown that the multi-algorithm approach can significantly optimize workload distribution among workers. # Conclusion The operational human resources workload balancing in the last mile delivery system is a complex problem that requires optimizing package assignments to workers. The multi-algorithm approach proposed uses a combination of distance and workload considerations to optimize package assignment to workers. # Results The proposal has been applied to a last mile delivery system operating in Azuqueca de Henares, Spain. The results have shown that the multi-algorithm approach can significantly optimize workload distribution among workers. # Future Work Future research may focus on validating the effectiveness of the multi-algorithm approach in different environments and experimenting with new algorithms to further improve package assignment to workers.