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An extended transportation problem: a DEA-based approach

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  • Alireza Amirteimoori

Abstract

The transportation problem is an important network structured linear programming problem that arises in several contexts and that has received a great deal of attention in the literature. The existing transportation problems are limited to consideration unit of shipping cost or profit along an arc. However, in many real applications, various attributes are usually considered in a transportation problem. The current paper, proposes an extension to this problem in the presence of multiple in-commensurate inputs and outputs for each arc. The concept of relative efficiency is defined for each possible transportation plan. Two linear programming models are proposed to determine the transportation plan with the maximum efficiency. A numerical example is used to illustrate the applicability of the approach. Copyright Springer-Verlag 2011

Suggested Citation

  • Alireza Amirteimoori, 2011. "An extended transportation problem: a DEA-based approach," 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 513-521, December.
    • Handle: RePEc:spr:cejnor:v:19:y:2011:i:4:p:513-521
    DOI: 10.1007/s10100-010-0140-0
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    References listed on IDEAS

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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. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, March.
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    Cited by:

    1. Mohammad Ali Raayatpanah & Salman Khodayifar & Thomas Weise & Panos Pardalos, 2022. "A novel approach to subgraph selection with multiple weights on arcs," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 242-268, August.
    2. Ching-Chin Chern & Tzi-Yuan Chou & Bo Hsiao, 2016. "Assessing the efficiency of supply chain scheduling algorithms using data envelopment analysis," Information Systems and e-Business Management, Springer, vol. 14(4), pages 823-856, November.
    3. M. Bagheri & A. Ebrahimnejad & S. Razavyan & F. Hosseinzadeh Lotfi & N. Malekmohammadi, 2022. "Fuzzy arithmetic DEA approach for fuzzy multi-objective transportation problem," Operational Research, Springer, vol. 22(2), pages 1479-1509, April.
    4. Yingying Shao & Gongbing Bi & Feng Yang & Qiong Xia, 2018. "Resource allocation for branch network system with considering heterogeneity based on DEA method," 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. 26(4), pages 1005-1025, December.
    5. Congcong Yang & Alfred Taudes & Guozhi Dong, 2017. "Efficiency analysis of European Freight Villages: three peers for benchmarking," 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. 25(1), pages 91-122, March.
    6. Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar, 2023. "A new branch and efficiency algorithm for an optimal design of the supply chain network in view of resilience, inequity and traffic congestion," Annals of Operations Research, Springer, vol. 321(1), pages 49-78, February.

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