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DEA-based production planning

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  • Du, Juan
  • Liang, Liang
  • Chen, Yao
  • Bi, Gong-bing
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    Abstract

    Production in large organizations with a centralized decision-making environment like supermarket chains or factories with many workshops, usually involves the participation of more than one individual unit, each contributing a part of the total production. This study is motivated by a production-planning problem regularly faced by the central decision-making unit to arrange new input and output plans for all individual units in the next production season when demand changes can be forecasted. Two planning ideas have been proposed in this paper. One is optimizing the average or overall production performance of the entire organization, measured by the CCR efficiency of the average input and output levels of all units. The other is simultaneously maximizing total outputs produced and minimizing total inputs consumed by all units. According to these two ideas, we develop two DEA-based production planning approaches to find the most preferred production plans. All these individual units, considered as decision-making units (DMUs), are supposed to be able to modify their input usages and output productions. A simple numerical example and a real world data set are used to illustrate these approaches.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 38 (2010)
    Issue (Month): 1-2 (February)
    Pages: 105-112

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    Handle: RePEc:eee:jomega:v:38:y:2010:i:1-2:p:105-112

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    Related research

    Keywords: Production plan Data envelopment analysis (DEA) Decision-making units (DMUs) Centralized decision-making environment Efficiency analysis;

    References

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    1. 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.
    2. Yu, Ming-Miin & Lin, Erwin T.J., 2008. "Efficiency and effectiveness in railway performance using a multi-activity network DEA model," Omega, Elsevier, vol. 36(6), pages 1005-1017, December.
    3. Botti, Laurent & Briec, Walter & Cliquet, Gérard, 2009. "Plural forms versus franchise and company-owned systems: A DEA approach of hotel chain performance," Omega, Elsevier, vol. 37(3), pages 566-578, June.
    4. Li, Yongjun & Liang, Liang & Chen, Yao & Morita, Hiroshi, 2008. "Models for measuring and benchmarking olympics achievements," Omega, Elsevier, vol. 36(6), pages 933-940, December.
    5. Marie Chazal & Elyès Jouini & Rabah Tahraoui, 2003. "Production Planning and Inventories Optimization : A Backward Approach in the Convex Storage Cost Case," GE, Growth, Math methods 0312002, EconWPA.
    6. Pekka Korhonen & Mikko Syrjänen, 2004. "Resource Allocation Based on Efficiency Analysis," Management Science, INFORMS, vol. 50(8), pages 1134-1144, August.
    7. Jouini, Elyès & Chazal, Marie & Tahraoui, Rabah, 2008. "Production Planning and Inventories Optimization: A Backward Approach in the Convex Storage Cost Case," Economics Papers from University Paris Dauphine 123456789/185, Paris Dauphine University.
    8. Beasley, J. E., 2003. "Allocating fixed costs and resources via data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 147(1), pages 198-216, May.
    9. Meng, Wei & Zhang, Daqun & Qi, Li & Liu, Wenbin, 2008. "Two-level DEA approaches in research evaluation," Omega, Elsevier, vol. 36(6), pages 950-957, December.
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    Citations

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    Cited by:
    1. Fang, Lei, 2013. "A generalized DEA model for centralized resource allocation," European Journal of Operational Research, Elsevier, vol. 228(2), pages 405-412.
    2. Amirteimoori, Alireza & Kordrostami, Sohrab, 2012. "Production planning in data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 140(1), pages 212-218.
    3. Li, Yongjun & Yang, Min & Chen, Ya & Dai, Qianzhi & Liang, Liang, 2013. "Allocating a fixed cost based on data envelopment analysis and satisfaction degree," Omega, Elsevier, vol. 41(1), pages 55-60.
    4. Samoilenko, Sergey & Osei-Bryson, Kweku-Muata, 2013. "Using Data Envelopment Analysis (DEA) for monitoring efficiency-based performance of productivity-driven organizations: Design and implementation of a decision support system," Omega, Elsevier, vol. 41(1), pages 131-142.
    5. Sahoo, Biresh K. & Tone, Kaoru, 2013. "Non-parametric measurement of economies of scale and scope in non-competitive environment with price uncertainty," Omega, Elsevier, vol. 41(1), pages 97-111.
    6. Milioni, Armando Zeferino & de Avellar, José Virgílio Guedes & Gomes, Eliane Gonçalves & Soares de Mello, João Carlos Correia Baptista, 2011. "An ellipsoidal frontier model: Allocating input via parametric DEA," European Journal of Operational Research, Elsevier, vol. 209(2), pages 113-121, March.
    7. Wang, Ying-Ming & Chin, Kwai-Sang, 2011. "The use of OWA operator weights for cross-efficiency aggregation," Omega, Elsevier, vol. 39(5), pages 493-503, October.
    8. Ramón, Nuria & Ruiz, José L. & Sirvent, Inmaculada, 2011. "Reducing differences between profiles of weights: A "peer-restricted" cross-efficiency evaluation," Omega, Elsevier, vol. 39(6), pages 634-641, December.
    9. Stewart, Theodor J., 2010. "Goal directed benchmarking for organizational efficiency," Omega, Elsevier, vol. 38(6), pages 534-539, December.
    10. Chang, Shyr-Juh & Hsiao, Hsing-Chin & Huang, Li-Hua & Chang, Hsihui, 2011. "Taiwan quality indicator project and hospital productivity growth," Omega, Elsevier, vol. 39(1), pages 14-22, January.

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