A new neuro-dominance rule for single machine tardiness problem


Cakar T.

COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2005, VOL 4, PROCEEDINGS, vol.3483, pp.1241-1250, 2005 (Journal Indexed in SCI) identifier

  • Publication Type: Article / Article
  • Volume: 3483
  • Publication Date: 2005
  • Title of Journal : COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2005, VOL 4, PROCEEDINGS
  • Page Numbers: pp.1241-1250

Abstract

We present a neuro-dominance rule for single machine total weighted tardiness problem. To obtain the neuro-dominance rule (NDR), backpropagation artificial neural network (BPANN) has been trained using 5000 data and also tested using 5000 another data. The proposed neurodominance rule provides a sufficient condition for local optimality. It has been proved that if any sequence violates the neuro-dominance rule then violating jobs are switched according to the total weighted tardiness criterion. The proposed neuro-dominance rule is compared to a number of competing heuristics and meta heuristics for a set of randomly generated problems. Our computational results indicate that the neuro-dominance rule dominates the heuristics and meta heuristics in all runs. Therefore, the neuro-dominance rule can improve the upper and lower bounding schemes.