A new neuro-dominance rule for single machine tardiness problem

Çakar T.

International Conference on Computational Science and Its Applications - ICCSA 2005, Singapore, 9 - 12 May 2005, vol.3483, pp.1241-1250, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 3483
  • Doi Number: 10.1007/11424925_129
  • Country: Singapore
  • Page Numbers: pp.1241-1250
  • Istanbul Gelisim University Affiliated: No

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 neuro-dominance 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. © Springer-Verlag Berlin Heidelberg 2005.