Deep learning-driven scheduling algorithm for a single machine problem minimizing the total tardiness

arXiv:2402.14847v1 Announce Type: cross
Abstract: In this paper, we investigate the use of the deep learning method for solving a well-known NP-hard single machine scheduling problem with the objective of minimizing the total tardiness. We propose a deep neural network that acts as a polynomial-time estimator of the criterion value used in a single-pass scheduling algorithm based on Lawler's decomposition and symmetric decomposition proposed by Della Croce et al. Essentially, the neural network guides the algorithm by estimating the best …

abstract algorithm arxiv cs.ai cs.lg deep learning deep neural network machine math.oc network neural network np-hard paper polynomial scheduling total type