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International Journal of Latest Research in Science and Technology

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Literature Review For Scheduling Problems

Research Paper Open Access

International Journal of Latest Research in Science and Technology Vol.1 Issue 1, pp 98-100,Year 2012

LITERATURE REVIEW FOR SCHEDULING PROBLEMS

Sanjeev Gill,Rajiv Kumar,

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Received : 12 June 2012; Accepted : 25 June 2012 ; Published : 30 June 2012

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Abstract

Present study in the paper is concerned with the development of new genetic operators to optimize the performance of the system. To improve the production facilities, a set of jobs are executed on the set of machines. For better performance there are large numbers of constraints. Process scheduling theory has been developed to meet all side constraints. Process Schedule is done in such a way that the resulting solution minimizes the given objective function. Many variants of the basic scheduling problem can be formulated by differentiating between machine environments, side constraints and objective functions. Genetic algorithm have been applied to OSPSP. The study shows that proposed operators shows better results

Key Words   
Genetic Algorithm,Meta heuristic,Scheduling,Optimization

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References
  1. Hanssmann , F. and Hess,S.W.(1960).A Linear Programming Approach to Production and Employment Scheduling. JSTOR: Management Technology, Vol. 1, No. 1 (Jan., 1960), pp. 46-51
  2. Held,M. and Karp,R.M.(1962). A dynamic programming approach to sequencing problem. SiAM, 1962.
  3. Ignall, E. and Schrage, L.E., (1965). Application of branch and bound techniques to some flow shop problems. Operation Research 13, 400–412.
  4. Bomberger.E.E.,(1966). A Dynamic Programming Approach to A Lot Size Scheduling Problem, JSTOR: Management Science, USA, Vol. 12, No. 11 (Jul., 1966), pp. 778-784
  5. Campbell, H.G., Dudek, R.A. and Smith, M.L., (1970). A heuristic algorithm for the n-job m-machine sequencing problem. Management Science 16(10), 169–174.
  6. Lockett, A.G. and Muhlemann, A.P., (1972). Technical notes: a scheduling Problem involving sequence dependent changeover times. Operation Research 20, 895- 902.
  7. Corwin, B. D. and Esogbue, A. O. (1974), Two machine flow shop scheduling problems with sequence dependent setup times: A dynamic programming approach. Naval Research Logistics Quarterly, 21: 515–524. doi: 10.1002/nav.3800210311.
  8. Holland, J. H. (1973). Genetic algorithms and the optimal allocation of trials. SIAM
    Journal on Computing, 2 (2), 88–105.
  9. Rinnooy Kan,A.(1976).Machine Scheduling Problem: Classification, Complexity and Computation. Martinus Nijhoff, Hague.
  10. Panwalkar S.S., Iskander, W., (1977). A Survey of Scheduling Rules. Operations Research 125(1), 45-62.
  11. Gupta, S. K., (1982). n jobs and m machines job shop problem with sequence dependent setup times. International Journal of Production Research. 20, 643-656.
  12. Kirkpatrick, S., Gelatt Jr, C.D.and Veechi, M.P., (1983). Optimization by simulated annealing. Science 220, 671–680.
  13. Gupta, J.N.D.,(1986). Flow shop schedules with sequence dependent setup times. Journal of the Operations Research Society of Japan 29, 206–219
  14. Hundal, T.S and Rajgopal, J.,(1988).An extension of palmer’s heuristic for the flow-shop scheduling problem. International Journal of Production Research 26, 1119–1124.
  15. McCormick, S.T., Pinedo, M.L., Shenker, S. and Wolf, B., (1989). Sequencing in an assembly line with blocking to minimize cycle time. Operations Research 37, 925– 935.
  16. Goldberg, D. E., Korb, B., & Deb, K. (1989). Messy genetic algorithms: Motivation,
    analysis, and first results. Complex Systems, 3 (5), 493–530
  17. Taillard, E.,( 1990). Some efficient heuristic methods for the flow shop sequencing problem. European Journal of Operational Research 47, 65–74.
  18. Beck,H., Drabblc,B. and Kirby,R.,(1991).Course Notes on Planning and Scheduling. Artificial Intelligence Applications Institute, University of Bdinburgh, 1991.
  19. Rajendran, C. and Chaudhuri, D.,( 1992). An efficient heuristic approach to the scheduling of jobs in a flow-shop. European Journal of Operational Research 61, 318– 325.
  20. Taillard, E., (1993). Benchmarks of basic scheduling problems. European Journal of Operation Research 64, 278–285.
  21. Zegordi, S.H., Itoh, K. and Enkawa, T.,(1995). Minimizing makespan for flow shop Scheduling by ombining simulated annealing with sequence knowledge. European Journal of Operational Research 85, 515–531.
  22. Marett, R. and Wright, M., (1996). A comparison of neighborhood search techniques for multi-objective combinatorial problems. Computers and Operations Research 23, 465–483.
  23. Pan, J.C.H., Fan, E.T., (1997). Two-machine flow shop scheduling to minimize total tardiness. International Journal of Systems Science 28, 405–14.
  24. Chen,H., Chu,C. and Proth,J.M.,(1998). An Improvement of the Lagrangean Relaxation Approach for Job Shop Scheduling: A Dynamic Programming Method, IEEE Transaction on Robotics and Automation,Vol.14,No.5, October pp 786-795.
  25. Voss S., Martello S., Osman I.H. and Rucairol C. (eds.), (1999). Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, Kluwer Academic Publishers.
  26. De Castro, L.N. and Timmis, J.I.,( 2003). Artificial immune systems as a novel soft computing paradigm. Soft Computing Journal 7(8), 526–544.
  27. Engin, O. and Doyen, A.,(2004). A new approach to solve hybrid flow shop scheduling problems by artificial immune system. Future Generation Computer Systems 20, 1083–1095.
  28. Rajendran, C. and Ziegler, H.,(2005). Two ant-colony algorithms for minimizing total flow time in permutation flow shops. Computers and Industrial Engineering 48, 789–797.
  29. Noorul Haq, A. and Radha Ramanan, T., (2006). A bi-criterian flow shops scheduling using artificial neural network. International Journal of Advanced Manufacturing Technology 30, 1132–1138.
  30. Chakraborty, U.K. and Laha, D., (2007). An improved heuristic for permutation flow shop scheduling. International Journal of Information and Communication Technology 1(1), 89 – 97.
  31. Naderi, B., Zandieh, M., Balagh, K.K.G. and Roshanaei, V., (2009A). An improved simulated annealing for hybrid flow shops with sequence-dependent setup and transportation times to minimize total completion time and total tardiness. Expert Systems with Applications: an International Journal 36(6), 9625-9633.
  32. Eren, T.,(2010). A Bicriteria M-Machine Flowshop Scheduling with Sequence- Dependent Setup Times. Applied Mathematical Modelling 34(2), 284 - 293.
To cite this article

Sanjeev Gill,Rajiv Kumar, , " Literature Review For Scheduling Problems ", International Journal of Latest Research in Science and Technology . Vol. 1, Issue 1, pp 98-100 , 2012

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