Three genetic algorithm approaches to the unrelated parallel machine scheduling problem with limited human resources

This paper addresses the unrelated parallel machine scheduling problem with limited and differently-skilled human resources. Firstly, the formulation of a Mixed Integer Linear Programming (MILP) model for solving the problem is provided. Then, three proper Genetic Algorithms (GAs) are presented, aiming to cope with larger sized issues. Numerical experiments put in evidence how all GAs proposed are able to approach the global optimum given by MILP model for small-sized instances. Moreover, a statistical comparison among proposed meta-heuristics algorithms is performed with reference to larger problems.