A genetic algorithm for robust schedules in a just-in-time environment
Faculty of Applied Economics
Antwerpen , 2003
Research paper / Faculty of Applied Economics UFSIA-RUCA ; 2003:8
University of Antwerp
Computing a schedule for a single machine problem is often difficult for irregular criteria, but when the data are uncertain, the problem is much more complicated. In this paper, we modify a genetic algorithm to compute robust schedules when release dates are subject to small variations. Two types of robustness are distinguished: quality robustness or robustness in the objective function space and solution robustness or robustness in the solution space. We show that the modified genetic algorithm can find solutions that are robust with respect to both types of robustness. Moreover, the risk associatedwith a specific solution can be easily evaluated. The modified genetic algorithm is applied to a just-in-time scheduling problem, a common problem in many industries.