@article{10902/28238,
year = {2022},
url = {https://hdl.handle.net/10902/28238},
abstract = {This paper addresses a variant of the job shop scheduling problem with total tardiness minimization where task durations and due dates are uncertain. This uncertainty is modelled with intervals. Different ranking methods for intervals are considered and embedded into a genetic algorithm. A new robustness measure is proposed to compare the different ranking methods and assess their capacity to predict ‘expected delays’ of jobs. Experimental results show that dealing with uncertainty during the optimization process yields more robust solutions. A sensitivity analysis also shows that the robustness of the solutions given by the solving method increases when the uncertainty grows.},
organization = {This research has been supported by the Spanish Government under research grants PID2019-106263RB-I00 and TIN2017-87600-P.},
publisher = {Logic Journal of the IGPL, 2022, jzac016},
title = {Robust schedules for tardiness optimization in job shop with interval uncertainty},
author = {Díaz, Hernán and Palacios, Juan José and Díaz, Irene and Vela, Camino R. and González Rodríguez, Inés},
}