IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v176y2007i3p1859-1873.html
   My bibliography  Save this article

A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem

Author

Listed:
  • Yang, Taho
  • Kuo, Yiyo
  • Cho, Chiwoon

Abstract

No abstract is available for this item.

Suggested Citation

  • Yang, Taho & Kuo, Yiyo & Cho, Chiwoon, 2007. "A genetic algorithms simulation approach for the multi-attribute combinatorial dispatching decision problem," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1859-1873, February.
    • Handle: RePEc:eee:ejores:v:176:y:2007:i:3:p:1859-1873
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(05)00883-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Valerie Botta-Genoulaz, 2000. "Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness," Post-Print hal-00398647, HAL.
    2. Petroni, Alberto & Rizzi, Antonio, 2002. "A fuzzy logic based methodology to rank shop floor dispatching rules," International Journal of Production Economics, Elsevier, vol. 76(1), pages 99-108, March.
    3. Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
    4. P. Pongcharoen & D. J. Stewardson & C. Hicks & P. M. Braiden, 2001. "Applying designed experiments to optimize the performance of genetic algorithms used for scheduling complex products in the capital goods industry," Journal of Applied Statistics, Taylor & Francis Journals, vol. 28(3-4), pages 441-455.
    5. Botta-Genoulaz, Valerie, 2000. "Hybrid flow shop scheduling with precedence constraints and time lags to minimize maximum lateness," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 101-111, March.
    6. Azadivar, Farhad & Tompkins, George, 1999. "Simulation optimization with qualitative variables and structural model changes: A genetic algorithm approach," European Journal of Operational Research, Elsevier, vol. 113(1), pages 169-182, February.
    7. Sarper, H. & Henry, M. C., 1996. "Combinatorial evaluation of six dispatching rules in a dynamic two-machine flow shop," Omega, Elsevier, vol. 24(1), pages 73-81, February.
    8. Rajendran, Chandrasekharan & Holthaus, Oliver, 1999. "A comparative study of dispatching rules in dynamic flowshops and jobshops," European Journal of Operational Research, Elsevier, vol. 116(1), pages 156-170, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fahimnia, Behnam & Sarkis, Joseph & Eshragh, Ali, 2015. "A tradeoff model for green supply chain planning:A leanness-versus-greenness analysis," Omega, Elsevier, vol. 54(C), pages 173-190.
    2. Ilkyeong Moon & Sanghyup Lee & Moonsoo Shin & Kwangyeol Ryu, 2016. "Evolutionary resource assignment for workload-based production scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 375-388, April.
    3. Kuo, Yiyo & Yang, Taho & Cho, Chiwoon & Tseng, Yao-Ching, 2008. "Using simulation and multi-criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(1), pages 40-56.
    4. Pickardt, Christoph W. & Hildebrandt, Torsten & Branke, Jürgen & Heger, Jens & Scholz-Reiter, Bernd, 2013. "Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems," International Journal of Production Economics, Elsevier, vol. 145(1), pages 67-77.
    5. Urlings, Thijs & Ruiz, Rubén & Stützle, Thomas, 2010. "Shifting representation search for hybrid flexible flowline problems," European Journal of Operational Research, Elsevier, vol. 207(2), pages 1086-1095, December.
    6. Yunna Tian & Dongni Li & Pengyu Zhou & Rongtao Guo & Zhaohe Liu, 2018. "An ACO-based hyperheuristic with dynamic decision blocks for intercell scheduling," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1905-1921, December.
    7. Branke, Juergen & Pickardt, Christoph W., 2011. "Evolutionary search for difficult problem instances to support the design of job shop dispatching rules," European Journal of Operational Research, Elsevier, vol. 212(1), pages 22-32, July.
    8. Tim Chen & Hendri Daleanu & Chi-Huey Wong* & J.C.-Y. Chen, 2019. "Mathematical Derives of Evolutionary Algorithms for Multiple Criteria Decision Making," Sumerianz Journal of Scientific Research, Sumerianz Publication, vol. 2(1), pages 5-11, 01-2019.
    9. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    10. Chiang, Tsung-Che & Fu, Li-Chen, 2009. "Using a family of critical ratio-based approaches to minimize the number of tardy jobs in the job shop with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 196(1), pages 78-92, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kuo, Yiyo & Yang, Taho & Cho, Chiwoon & Tseng, Yao-Ching, 2008. "Using simulation and multi-criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(1), pages 40-56.
    2. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
    3. Quadt, Daniel & Kuhn, Heinrich, 2007. "A taxonomy of flexible flow line scheduling procedures," European Journal of Operational Research, Elsevier, vol. 178(3), pages 686-698, May.
    4. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.
    5. Allahverdi, Ali & Ng, C.T. & Cheng, T.C.E. & Kovalyov, Mikhail Y., 2008. "A survey of scheduling problems with setup times or costs," European Journal of Operational Research, Elsevier, vol. 187(3), pages 985-1032, June.
    6. Theodor Freiheit & Wei Li, 2017. "The effect of work content imbalance and its interaction with scheduling method on sequential flow line performance," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2791-2805, May.
    7. Marco Schulze & Julia Rieck & Cinna Seifi & Jürgen Zimmermann, 2016. "Machine scheduling in underground mining: an application in the potash industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(2), pages 365-403, March.
    8. Carlos Paternina-Arboleda & Jairo Montoya-Torres & Milton Acero-Dominguez & Maria Herrera-Hernandez, 2008. "Scheduling jobs on a k-stage flexible flow-shop," Annals of Operations Research, Springer, vol. 164(1), pages 29-40, November.
    9. Petroni, Alberto & Rizzi, Antonio, 2002. "A fuzzy logic based methodology to rank shop floor dispatching rules," International Journal of Production Economics, Elsevier, vol. 76(1), pages 99-108, March.
    10. Madiha Harrabi & Olfa Belkahla Driss & Khaled Ghedira, 2021. "A hybrid evolutionary approach to job-shop scheduling with generic time lags," Journal of Scheduling, Springer, vol. 24(3), pages 329-346, June.
    11. Hicks, Christian, 2006. "A Genetic Algorithm tool for optimising cellular or functional layouts in the capital goods industry," International Journal of Production Economics, Elsevier, vol. 104(2), pages 598-614, December.
    12. W L Pearn & S H Chung & M H Yang & K P Shiao, 2008. "Solution strategies for multi-stage wafer probing scheduling problem with reentry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 637-651, May.
    13. F Sivrikaya şerifoğlu & G Ulusoy, 2004. "Multiprocessor task scheduling in multistage hybrid flow-shops: a genetic algorithm approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 504-512, May.
    14. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    15. Pongcharoen, P. & Promtet, W. & Yenradee, P. & Hicks, C., 2008. "Stochastic Optimisation Timetabling Tool for university course scheduling," International Journal of Production Economics, Elsevier, vol. 112(2), pages 903-918, April.
    16. Janiak, Adam & Kozan, Erhan & Lichtenstein, Maciej & Oguz, Ceyda, 2007. "Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion," International Journal of Production Economics, Elsevier, vol. 105(2), pages 407-424, February.
    17. Amin-Naseri, Mohammad Reza & Beheshti-Nia, Mohammad Ali, 2009. "Hybrid flow shop scheduling with parallel batching," International Journal of Production Economics, Elsevier, vol. 117(1), pages 185-196, January.
    18. Anurag Agarwal & Varghese S. Jacob & Hasan Pirkul, 2006. "An Improved Augmented Neural-Network Approach for Scheduling Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 119-128, February.
    19. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.
    20. Julian Yeomans, 2011. "Efficient generation of alternative perspectives in public environmental policy formulation: applying co-evolutionary simulation–optimization to municipal solid waste management," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 391-413, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:176:y:2007:i:3:p:1859-1873. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.