This paper addresses the unrelated parallel machine scheduling problem with limited human resources. Firstly, the formulation of a Mixed Integer Linear Programming (MILP) model for optimally solving the problem is provided. Then, a proper genetic algorithm (GA) is presented aiming to cope with larger sized issues. Numerical experiments put in evidence how both the number of workers and the number of machines employed within the production system play a key role in minimizing makespan. Moreover, obtained results highlight the effectiveness and the efficiency of the proposed GA, under the quality of solution and the computationa l burden viewpoints.
Makespan Minimization of Unrelated Parallel Machines with Limited Human Resources
COSTA, ANTONIO;FICHERA, Sergio
2013-01-01
Abstract
This paper addresses the unrelated parallel machine scheduling problem with limited human resources. Firstly, the formulation of a Mixed Integer Linear Programming (MILP) model for optimally solving the problem is provided. Then, a proper genetic algorithm (GA) is presented aiming to cope with larger sized issues. Numerical experiments put in evidence how both the number of workers and the number of machines employed within the production system play a key role in minimizing makespan. Moreover, obtained results highlight the effectiveness and the efficiency of the proposed GA, under the quality of solution and the computationa l burden viewpoints.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.