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Original Articles

A hybrid computer simulation-artificial neural network algorithm for optimisation of dispatching rule selection in stochastic job shop scheduling problems

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Pages 551-566 | Received 15 Jun 2010, Accepted 26 Aug 2010, Published online: 14 Jun 2011

References

  • Ahmadizar , F , Ghazanfari , M and Ghomi , SMTF . 2010 . Group shops scheduling with makespan criterion subject to random release dates and processing times . Computers and Operations Research , 37 ( 1 ) : 152 – 162 .
  • Alpay , Ş and Yüzügüllü , N . 2009 . Dynamic job shop scheduling for missed due date performance . International Journal of Production Research , 47 ( 15 ) : 4047 – 4062 .
  • Baker , KR and Trietsch , D . 2009 . Principles of sequencing and scheduling , Hoboken , NJ : Wiley .
  • Balut , SJ . 1973 . Scheduling to minimize the number of late jobs when set-up and processing times are uncertain . Management Science , 19 ( 11 ) : 1283 – 1288 .
  • Fonseca , DJ , Navaresse , DO and Moynihan , GP . 2003 . Simulation meta-modeling through artificial neural networks . Engineering Applications of Artificial Intelligence , 16 ( 3 ) : 177 – 183 .
  • Gao , J , Sun , L and Gen , M . 2008 . A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems . Computers and Operations Research , 35 ( 9 ) : 2892 – 2907 .
  • Garey , M , Johnson , D and Sethi , R . 1976 . The complexity of flow shop and job shop scheduling . Mathematics of Operations Research , 1 ( 2 ) : 117 – 129 .
  • Ginzburg , DG and Gonik , A . 2002 . Optimal job-shop scheduling with random operations and cost objectives . International Journal of Production Economics , 76 ( 2 ) : 147 – 157 .
  • Gourgand , M , Grangeon , N and Norre , S . 2003 . A contribution to the stochastic flow shop scheduling problem . European Journal of Operational Research , 151 ( 2 ) : 415 – 433 .
  • Gu , J , Gu , X and Gu , M . 2009 . A novel parallel quantum genetic algorithm for stochastic job shop scheduling . Journal of Mathematical Analysis and Applications , 355 ( 1 ) : 63 – 81 .
  • Gu , J . 2010 . A novel competitive co-evolutionary quantum genetic algorithm for stochastic job shop scheduling problem . Computers and Operations Research , 37 ( 5 ) : 927 – 937 .
  • Gupta , AK and Sivakumar , AI . 2006 . Optimization of due-date objectives in scheduling semiconductor batch manufacturing . International Journal of Machine Tools and Manufacture , 46 ( 12–13 ) : 1671 – 1679 .
  • Haykin , S . 1999 . Neural networks , Englewood Cliffs , NJ : Prentice-Hall .
  • Hill , T and Remus , W . 1994 . Neural network models for intelligent support of managerial decision making . Decision Support Systems , 11 ( 5 ) : 449 – 459 .
  • Hornik , K , Stinchcombe , M and White , H . 1989 . Multilayer feed-forward networks are universal approximators . Neural Network , 2 ( 5 ) : 359 – 366 .
  • Jeong , KC and Kim , YD . 1998 . A real-time scheduling mechanism for a flexible manufacturing system: using simulation and dispatching rules . International Journal of Production Research , 36 ( 9 ) : 2609 – 2626 .
  • Kadipasaoglu , SN , Xiang , W and Khumawala , BM . 1997 . A comparison of sequencing rules in static and dynamic hybrid flow systems . International Journal of Production Research , 35 ( 5 ) : 1359 – 1384 .
  • Kuo , Y . 2007 . Simulation meta-model development using uniform design and neural networks for automated material handling systems in semiconductor wafer fabrication . Simulation Modelling Practice and Theory , 15 ( 8 ) : 1002 – 1015 .
  • Lee , CY , Piramuthu , S and Tsai , YK . 1997 . Job shop scheduling with a genetic algorithm and machine learning . International Journal of Production Research , 35 ( 4 ) : 1171 – 1191 .
  • Lei , D . 2008 . A Pareto archive particle swarm optimization for multi-objective job shop scheduling . Computers and Industrial Engineering , 54 ( 4 ) : 960 – 971 .
  • Lejmi , T and Sabuncuoglu , I . 2002 . Effect of load, processing time and due date variation on the effectiveness of scheduling rules . International Journal of Production Research , 40 ( 4 ) : 945 – 974 .
  • Li , W and Glazebrook , KD . 1998 . On stochastic machine scheduling with general distributional assumptions . European Journal of Operational Research , 105 ( 3 ) : 525 – 536 .
  • Li , X . 2007 . Job scheduling to minimize the weighted waiting time variance of jobs . Computers and Industrial Engineering , 52 ( 1 ) : 41 – 56 .
  • Metan , G , Sabuncuoglu , I and Pierreval , H . 2010 . Real time selection of scheduling rules and knowledge extraction via dynamically controlled data mining . International Journal of Production Research , 48 ( 23 ) : 6909 – 6938 .
  • Naderi , B , Fatemi Ghomi , SMT and Aminnayeri , M . 2010 . A high performing metaheuristic for job shop scheduling with sequence-dependent setup times . Applied Soft Computing , 10 ( 3 ) : 703 – 710 .
  • Pritsker , AAB and O’Reilly , JJ . 1999 . Simulation with Visual SLAM® and AweSim® , New York : John Wiley and Sons .
  • Roshanaei , V . 2009 . A variable neighborhood search for job shop scheduling with set-up times to minimize makespan . Future Generation Computer Systems , 25 ( 6 ) : 654 – 661 .
  • Singer , M . 2000 . Forecasting policies for scheduling a stochastic due date job shop . International Journal of Production Research , 38 ( 15 ) : 3623 – 3637 .
  • Soroush , HM . 2010 . Solving a stochastic single machine problem with initial idle time and quadratic objective . Computers and Operations Research , 37 ( 7 ) : 1328 – 1347 .
  • Tavakkoli-Moghaddam , R and Daneshmand-Mehr , M . 2005 . A computer simulation model for job shop scheduling problems minimizing makespan . Computers and Industrial Engineering , 48 ( 4 ) : 811 – 823 .
  • Tavakkoli-Moghaddam , R . 2005 . A hybrid method for solving stochastic job shop scheduling problems . Applied Mathematics and Computation , 170 ( 1 ) : 185 – 206 .
  • Topaloglu , S and Kilincli , G . 2009 . A modified shifting bottleneck heuristic for the reentrant job shop scheduling problem with makespan minimization . International Journal of Advanced Manufacturing Technology , 44 ( 7–8 ) : 781 – 794 .
  • Vinod , V and Sridharan , R . 2008 . Dynamic job-shop scheduling with sequence-dependent setup times: simulation modeling and analysis . International Journal of Advanced Manufacturing Technology , 36 ( 3–4 ) : 355 – 372 .
  • Vinod , V and Sridharan , R . 2009 . Simulation-based meta-models for scheduling a dynamic job shop with sequence-dependent setup times . International Journal of Production Research , 47 ( 6 ) : 1425 – 1447 .
  • Wu , X and Zhou , X . 2008 . Stochastic scheduling to minimize expected maximum lateness . European Journal of Operational Research , 190 ( 1 ) : 103 – 115 .
  • Yoshitomi , Y and Yamaguchi , R . 2003 . A genetic algorithm and the Monte Carlo method for stochastic job-shop scheduling . International Transactions in Operational Research , 10 ( 6 ) : 577 – 596 .
  • Zimmermann , HG . Neuneier, R., Grothmann, R., 2002. Undershooting: modeling dynamical systems by time grid refinements. In: Proceedings of the European symposium on artificial neural networks (ESANN'2002), 24–26 April, Bruges, Belgium, 395–400

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