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A New Neuro-Dominance Rule for Single Machine Tardiness Problem

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Computational Science and Its Applications – ICCSA 2005 (ICCSA 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3483))

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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.

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References

  1. Jensen, J.B., Philipoom, P.R., Malhotra, M.K.: Evaluation of scheduling Rules with commensurate customer priorities in job shops. Journal of operation management 13, 213–228 (1995)

    Article  Google Scholar 

  2. Lawler, E.L.: A “Pseudopolynomial” algorithm for sequencing job to minimize total tardiness. Annals of Discrete Mathematics 1, 331–342 (1997)

    Article  Google Scholar 

  3. Chambers, R.J., Carraway, R.L., Lowe, T.J., Morin, T.L.: Dominance and decomposition heuristics for single machine scheduling. Operation Research 39, 639–647 (1991)

    Article  MATH  Google Scholar 

  4. Emmons, H.: One machine sequencing to minimize certain functions of job tardiness. Operation Research 17, 701–715 (1969)

    Article  MATH  MathSciNet  Google Scholar 

  5. Fisher, M.L.: A dual algorithm for the one-machine scheduling problem. Mathematical Programming 11, 229–251 (1976)

    Article  MathSciNet  Google Scholar 

  6. Potts, C.N., Van Wassenhove, L.N.: A Branch and bound algorithmfor total weighted tardiness problem. Operation Research 33, 363–377 (1985)

    Article  MATH  Google Scholar 

  7. Potts, C.N., Van Wassenhove, L.N.: Dynamic programming and decomposition approaches for the single machine total tardiness problem. European Journal of Operation Research 32, 405–414 (1987)

    Article  MATH  Google Scholar 

  8. Rinnooy Kan, A.H.G., Lageweg, B.J., Lenstra, J.K.: Minimizing total costs in one machine scheduling. Operations Research 23, 908–927 (1975)

    Article  MATH  MathSciNet  Google Scholar 

  9. Abdul-Razaq, T.S., Potts, C.N., Van Wassenhove, L.N.: A survey of algorithms for the single machine total weighted tardiness scheduling problem. Discrete Applied Mathematics 26, 235–253 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  10. Hoogeveen, J.A., Van de Velde, S.L.: Stronger Lagrangian bounds by use of slack variables: applications to machine scheduling problems. Mathematical Programming 195(70), 173–190

    Google Scholar 

  11. Szwarc, W.: Adjacent orderings in single machine scheduling with earliness and tardiness penalties. Naval research Logistics 40, 229–243 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  12. Szwarc, W., Liu, J.J.: Weighted Tardines single machine scheduling with proportional weights. Management Science 39, 626–632 (1993)

    Article  MATH  Google Scholar 

  13. Vepsalainen, A.P.J., Morton, T.E.: Priority rules for job shops with weighted tardiness cost. Management Science 33, 1035–1047 (1987)

    Article  Google Scholar 

  14. Sabuncuoglu, I., Gurgun, B.: A neural network model for scheduling problems. European Journal of Operational research 93(2), 288–299 (1996)

    Article  MATH  Google Scholar 

  15. Akturk, M.S., Ozdemir, D.: A new dominance rule to minimize total weighted tardiness with unequal release date. European Journal of Operational research 135, 394–412 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  16. Akturk, M.S., Yidirim, M.B.: A new lower bounding scheme for the total weighted tardiness problem. Computers and Operational Research 25(4), 265–278 (1998)

    Article  MATH  Google Scholar 

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Authors and Affiliations

  1. Department of Industrial Engineering, Sakarya University Engineering Faculty, 54187, Adapazarı, Turkey

    Tarık Çakar

Authors
  1. Tarık Çakar
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  2. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  5. Institute of High Performance Computing, IHCP, 1 Science Park Road, 01-01 The Capricorn, Singapore Science Park II, 117528, Singapore

    Heow Pueh Lee

  6. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  7. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  8. OptimaNumerics Ltd, Belfast, United Kingdom

    Chih Jeng Kenneth Tan

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© 2005 Springer-Verlag Berlin Heidelberg

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Çakar, T. (2005). A New Neuro-Dominance Rule for Single Machine Tardiness Problem. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2005. ICCSA 2005. Lecture Notes in Computer Science, vol 3483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11424925_129

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  • DOI: https://doi.org/10.1007/11424925_129

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25863-6

  • Online ISBN: 978-3-540-32309-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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