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A facility location and installation of resources model for level of repair analysis

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  • Brick, Eduardo Siqueira
  • Uchoa, Eduardo

Abstract

The Level of Repair Analysis - LORA - is an analytic methodology aimed at determining: (i) the optimal location of facilities that compose a maintenance structure; (ii) the quantity of required resources in each facility; and (iii) the best repair policies, i.e., rules that determine if a given component should be discarded or repaired, and where those actions should take place. This work presents a mixed-integer programming model for LORA that is more comprehensive than others in the literature, being suitable to many practical situations. The model was applied to 15 substantial real world problems, and considering distinct maintenance policies to some of them, resulted in 22 different solutions, all of which could be achieved by a commercial Mixed-Integer Programming (MIP) solver in reasonable times.

Suggested Citation

  • Brick, Eduardo Siqueira & Uchoa, Eduardo, 2009. "A facility location and installation of resources model for level of repair analysis," European Journal of Operational Research, Elsevier, vol. 192(2), pages 479-486, January.
  • Handle: RePEc:eee:ejores:v:192:y:2009:i:2:p:479-486
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    References listed on IDEAS

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    1. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    2. Klose, Andreas & Drexl, Andreas, 2005. "Facility location models for distribution system design," European Journal of Operational Research, Elsevier, vol. 162(1), pages 4-29, April.
    3. Alfredsson, Patrik, 1997. "Optimization of multi-echelon repairable item inventory systems with simultaneous location of repair facilities," European Journal of Operational Research, Elsevier, vol. 99(3), pages 584-595, June.
    4. Barros, Lilian & Riley, Michael, 2001. "A combinatorial approach to level of repair analysis," European Journal of Operational Research, Elsevier, vol. 129(2), pages 242-251, March.
    5. Barros, Lilian L. & Riley, Michael & Brown, David, 2001. "Special millennium issue of the EJOR: A global view of industrial logistics," European Journal of Operational Research, Elsevier, vol. 129(2), pages 231-234, March.
    6. ReVelle, C.S. & Eiselt, H.A. & Daskin, M.S., 2008. "A bibliography for some fundamental problem categories in discrete location science," European Journal of Operational Research, Elsevier, vol. 184(3), pages 817-848, February.
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    Cited by:

    1. Ghaddar, Bissan & Sakr, Nizar & Asiedu, Yaw, 2016. "Spare parts stocking analysis using genetic programming," European Journal of Operational Research, Elsevier, vol. 252(1), pages 136-144.
    2. Basten, R.J.I. & van der Heijden, M.C. & Schutten, J.M.J., 2011. "Practical extensions to a minimum cost flow model for level of repair analysis," European Journal of Operational Research, Elsevier, vol. 211(2), pages 333-342, June.
    3. Basten, R.J.I. & van der Heijden, M.C. & Schutten, J.M.J., 2012. "Joint optimization of level of repair analysis and spare parts stocks," European Journal of Operational Research, Elsevier, vol. 222(3), pages 474-483.
    4. Ma, N., 2014. "Optimal scope of supply chain network & operations design," Other publications TiSEM e6187708-b664-44bf-aef8-f, Tilburg University, School of Economics and Management.
    5. Manish Rawat & Bhupesh Kumar Lad, 2016. "Simultaneous selection of reliability design and level of repair for fleet systems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(2), pages 138-155, June.

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