GRASP for Minimizing the Ergonomic Risk Range in Mixed-Model Assembly Lines
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  • 关键词:GRASP ; MILP ; Assembly line balancing problem ; Ergonomic risk
  • 刊名:Lecture Notes in Computer Science
  • 出版年:2016
  • 出版时间:2016
  • 年:2016
  • 卷:9868
  • 期:1
  • 页码:397-407
  • 全文大小:138 KB
  • 参考文献:1.Otto, A., Scholl, A.: Incorporating ergonomic risks into assembly line balancing. Eur. J. Oper. Res. 212(2), 277–286 (2011). doi:10.​1016/​j.​ejor.​2011.​01.​056 MathSciNet CrossRef
    2.Battini, D., Delorme, X., Dolgui, A., Sgarbossa, F.: Assembly line balancing with ergonomics paradigms: two alternative methods. IFAC-PapersOnLine 48(3), 586–591 (2015). doi:10.​1016/​j.​ifacol.​2015.​06.​145 CrossRef
    3.Bautista, J., Batalla, C., Alfaro, R.: Incorporating ergonomics factors into the TSALBP. In: Emmanouilidis, C., Taisch, M., Kiritsis, D. (eds.) Advances in Production Management Systems. IFIP AICT, vol. 397, pp. 413–420. Springer, Heidelberg (2013)
    4.Batalla, C.: Métodos para la incorporación del riesgo ergonómico en líneas de montaje de productos mixtos. Thesis for Ph.D. in Industrial Engineering - Universitat Politècnica de Catalunya BarcelonaTech (2015). https://​www.​researchgate.​net/​publication/​280235683
    5.Bautista, J., Batalla-García, C., Alfaro-Pozo, R.: Models for assembly line balancing by temporal, spatial and ergonomic risk attributes. Eur. J. Oper. Res. 251(3), 814–829 (2016). doi:10.​1016/​j.​ejor.​2015.​12.​042 MathSciNet CrossRef
    6.Bautista, J., Alfaro-Pozo, R., Batalla-García, C.: GRASP approach to a min-max problem of ergonomic risk in restricted assembly lines. In: Puerta, J.M., et al. (eds.) CAEPIA 2015. LNCS, vol. 9422, pp. 278–288. Springer, Heidelberg (2015). doi:10.​1007/​978-3-319-24598-0_​25 CrossRef
    7.Battaïa, O., Dolgui, A.: A taxonomy of line balancing problems and their solution approaches. Int. J. Prod. Econ. 142(2), 259–277 (2013). doi:10.​1016/​j.​ijpe.​2012.​10.​020 CrossRef
    8.Chica, M., Cordón, O., Damas, S., Bautista, J.: Multiobjective constructive heuristics for the 1/3 variant of the time and space assembly line balancing problem: ACO and random greedy search. Inf. Sci. 180(18), 3465–3487 (2010). doi:10.​1016/​j.​ins.​2010.​05.​033 MathSciNet CrossRef
    9.Chica, M., Cordón, O., Damas, S., Bautista, J.: A multiobjective GRASP for the 1/3 variant of the time and space assembly line balancing problem. In: García-Pedrajas, N., Herrera, F., Fyfe, C., Benítez, J.M., Ali, M. (eds.) IEA/AIE 2010, Part III. LNCS, vol. 6098, pp. 656–665. Springer, Heidelberg (2010). http://​dx.​doi.​org/​10.​1007/​978-3-642-13033-5_​67 CrossRef
    10.Chica, M., Cordón, O., Damas, S., Bautista, J.: Including different kinds of preferences in a multiobjective and algorithm for time and space assembly line balancing on different Nissan scenarios. Expert Syst. Appl. 38(1), 709–720 (2011). doi:10.​1016/​j.​eswa.​2010.​07.​023 CrossRef
  • 作者单位:Joaquín Bautista (20)
    Rocío Alfaro-Pozo (20)
    Cristina Batalla-García (20)

    20. Research Group OPE-PROTHIUS, Dpto. de Organización de Empresas, Universitat Politècnica de Catalunya BarcelonaTech (UPC), Avda. Diagonal, 647, 08028, Barcelona, Spain
  • 丛书名:Advances in Artificial Intelligence
  • ISBN:978-3-319-44636-3
  • 刊物类别:Computer Science
  • 刊物主题:Artificial Intelligence and Robotics
    Computer Communication Networks
    Software Engineering
    Data Encryption
    Database Management
    Computation by Abstract Devices
    Algorithm Analysis and Problem Complexity
  • 出版者:Springer Berlin / Heidelberg
  • ISSN:1611-3349
  • 卷排序:9868
文摘
This research examines an assembly line balancing problem and compares the linear programing with a Greedy Randomized Adaptive Search Procedure (GRASP). The problem focuses on minimizing the absolute average deviation for the ergonomic risk between the set of workstations of the line, considering a fixed cycle time and an available space per station. However, the final objective is to obtain line configurations with the lowest possible ergonomic risk, and the lowest discrepancy for the risk level between all stations. Although GRASP does not win linear programing, in all cases, it shows competitive.

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