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RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks

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  • Grigoroudis, Evangelos
  • Petridis, Konstantinos
  • Arabatzis, Garyfallos

Abstract

The optimal design of supply chain networks is often examined based on one or more economic or other criteria (e.g., cost, profit environmental impact, danger, time). However, the efficiency of the derived solutions is often ignored. In this work, a recursive DEA (RDEA) algorithm is presented, which introduces a different way of designing a supply chain network. The selection of possible installed facilities is based on minimum cost and maximum efficiency, through a MILP model. Optimal supply chain structure is obtained when the termination criterion is met, yielding only the efficient solutions, while simultaneously reducing the overall cost. An application of this RDEA algorithm to a biomass supply chain is examined. A comparative study is also presented, demonstrating the results obtained when solving the MILP without the proposed algorithm and with the use of an RDEA.

Suggested Citation

  • Grigoroudis, Evangelos & Petridis, Konstantinos & Arabatzis, Garyfallos, 2014. "RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks," Renewable Energy, Elsevier, vol. 71(C), pages 113-122.
    • Handle: RePEc:eee:renene:v:71:y:2014:i:c:p:113-122
    DOI: 10.1016/j.renene.2014.05.001
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    Cited by:

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    2. Konstantinos Petridis, 2022. "Spatio-temporal efficiency measurement under undesirable outputs using multi-objective programming: a GAMS representation," Annals of Operations Research, Springer, vol. 311(2), pages 1183-1202, April.
    3. Konstantinos Ioannou & Georgios Tsantopoulos & Garyfallos Arabatzis & Zacharoula Andreopoulou & Eleni Zafeiriou, 2018. "A Spatial Decision Support System Framework for the Evaluation of Biomass Energy Production Locations: Case Study in the Regional Unit of Drama, Greece," Sustainability, MDPI, vol. 10(2), pages 1-22, February.
    4. Azadeh, Ali & Vafa Arani, Hamed, 2016. "Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach," Renewable Energy, Elsevier, vol. 93(C), pages 383-403.
    5. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    6. Bo Yan & Zhuo Chen & Hongyuan Li, 2019. "Evaluation of agri-product supply chain competitiveness based on extension theory," Operational Research, Springer, vol. 19(2), pages 543-570, June.
    7. Georgios Digkas & Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis & Ali Emrouznejad, 2020. "Measuring Spatio-temporal Efficiency: An R Implementation for Time-Evolving Units," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 843-864, December.
    8. Somayeh Soheilirad & Kannan Govindan & Abbas Mardani & Edmundas Kazimieras Zavadskas & Mehrbakhsh Nilashi & Norhayati Zakuan, 2018. "Application of data envelopment analysis models in supply chain management: a systematic review and meta-analysis," Annals of Operations Research, Springer, vol. 271(2), pages 915-969, December.
    9. Konstantinos Petridis & Prasanta Kumar Dey & Ali Emrouznejad, 2017. "A branch and efficiency algorithm for the optimal design of supply chain networks," Annals of Operations Research, Springer, vol. 253(1), pages 545-571, June.
    10. Toklu, E., 2017. "Biomass energy potential and utilization in Turkey," Renewable Energy, Elsevier, vol. 107(C), pages 235-244.
    11. Konstantinos Petridis & Garyfallos Arabatzis & Angelo Sifaleras, 2020. "Mathematical optimization models for fuelwood production," Annals of Operations Research, Springer, vol. 294(1), pages 59-74, November.
    12. Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar & Erfan Babaee Tirkolaee, 2022. "Performance Evaluation of Omni-Channel Distribution Network Configurations considering Green and Transparent Criteria under Uncertainty," Sustainability, MDPI, vol. 14(19), pages 1-15, October.
    13. Milad Kolagar & Seyed Mohammad Hassan Hosseini & Ramin Felegari & Parviz Fattahi, 2020. "Policy-making for renewable energy sources in search of sustainable development: a hybrid DEA-FBWM approach," Environment Systems and Decisions, Springer, vol. 40(4), pages 485-509, December.
    14. 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.
    15. Liu, Liwei & Ye, Junhong & Zhao, Yufei & Zhao, Erdong, 2015. "The plight of the biomass power generation industry in China – A supply chain risk perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 680-692.
    16. Petridis, Konstantinos & Tampakoudis, Ioannis & Drogalas, George & Kiosses, Nikolaos, 2022. "A Support Vector Machine model for classification of efficiency: An application to M&A," Research in International Business and Finance, Elsevier, vol. 61(C).

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