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Empirical validation of an activity-based optimization system

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  • Singer, Marcos
  • Donoso, Patricio

Abstract

We present an optimization model for steel manufacturing, whose objective function depends on activity-based costing (ABC). The constraints describe the capacity and the material balance, the product-dependent yield and the electrical balance, for all the activities of the plant. For the model to be reliable, one should validate that it accurately expresses the objective function of the user, and that it defines with precision the constraints that determine the feasible solutions. We validate the cost estimation by empirically testing how accurately it can predict future expenditures. We validate the constraints by comparing the polyhedron they generate with the production possibility set obtained with data envelopment analysis (DEA). We show the model implemented and validated in a Chilean steel manufacturer. The tests prove the model reliable enough for defining the product mix, and for evaluating investments and sourcing alternatives.

Suggested Citation

  • Singer, Marcos & Donoso, Patricio, 2008. "Empirical validation of an activity-based optimization system," International Journal of Production Economics, Elsevier, vol. 113(1), pages 335-345, May.
  • Handle: RePEc:eee:proeco:v:113:y:2008:i:1:p:335-345
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    References listed on IDEAS

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    1. Homburg, Carsten, 2005. "Using relative profits as an alternative to activity-based costing," International Journal of Production Economics, Elsevier, vol. 95(3), pages 387-397, March.
    2. repec:bla:joares:v:36:y:1998:i:1:p:129-142 is not listed on IDEAS
    3. E. Grifell-Tatjé & C. A. K. Lovell, 1999. "Profits and Productivity," Management Science, INFORMS, vol. 45(9), pages 1177-1193, September.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Goutam Dutta & Robert Fourer, 2001. "A Survey of Mathematical Programming Applications in Integrated Steel Plants," Manufacturing & Service Operations Management, INFORMS, vol. 3(4), pages 387-400.
    6. Boons, Arnick N. A. M., 1998. "Product costing for complex manufacturing systems," International Journal of Production Economics, Elsevier, vol. 55(3), pages 241-255, August.
    7. George B. Kleindorfer & Liam O'Neill & Ram Ganeshan, 1998. "Validation in Simulation: Various Positions in the Philosophy of Science," Management Science, INFORMS, vol. 44(8), pages 1087-1099, August.
    8. Fourer, Robert & Dutta, Goutam, 2000. "A Survey of Mathematical Programming Applications In Integrated Steel Plants," IIMA Working Papers WP2000-06-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    9. Singer, Marcos & Donoso, Patricio & Poblete, Francisco, 2002. "Semi-autonomous planning using linear programming in the Chilean General Treasury," European Journal of Operational Research, Elsevier, vol. 140(2), pages 517-529, July.
    10. Tang, Lixin & Liu, Jiyin & Rong, Aiying & Yang, Zihou, 2001. "A review of planning and scheduling systems and methods for integrated steel production," European Journal of Operational Research, Elsevier, vol. 133(1), pages 1-20, August.
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    Cited by:

    1. Askarany, Davood & Yazdifar, Hassan & Askary, Saeed, 2010. "Supply chain management, activity-based costing and organisational factors," International Journal of Production Economics, Elsevier, vol. 127(2), pages 238-248, October.
    2. Tsai, Wen-Hsien & Lai, Chien-Wen & Tseng, Li-Jung & Chou, Wen-Chin, 2008. "Embedding management discretionary power into an ABC model for a joint products mix decision," International Journal of Production Economics, Elsevier, vol. 115(1), pages 210-220, September.
    3. Askarany, Davood & Yazdifar, Hassan, 2012. "An investigation into the mixed reported adoption rates for ABC: Evidence from Australia, New Zealand and the UK," International Journal of Production Economics, Elsevier, vol. 135(1), pages 430-439.

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