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A New Stochastic MCDM Approach Based on COPRAS

Author

Listed:
  • Yelda Ayrim

    (Department of Industrial Engineering, Başkent University, Eskişehir Yolu 20.km Bağlica, Kampüsü 06970, Ankara, Turkey)

  • Kumru Didem Atalay

    (Department of Industrial Engineering, Başkent University, Eskişehir Yolu 20.km Bağlica, Kampüsü 06970, Ankara, Turkey)

  • Gülin Feryal Can

    (Department of Industrial Engineering, Başkent University, Eskişehir Yolu 20.km Bağlica, Kampüsü 06970, Ankara, Turkey)

Abstract

This study proposes a novel integrated Complex Proportional Assessment (COPRAS) approach by using stochastic decision process named as Stochastic COPRAS (COPRAS-S) to increase the evaluation performance of COPRAS. In COPRAS-S, criteria importance weights and the performance values of alternatives are determined by generating random numbers from uniform distribution in a range of minimum and maximum values of a limited number of decision-maker evaluations. Thus, the numbers of experts are increased and decision-making process is performed in an effective way because different opinions are incorporated. In addition, randomness feature brought with vagueness in decision is modeled in this process. A special normalization approach based on standard deviation is also implemented in COPRAS-S. In this way, cost and benefit type criteria are evaluated in a different way. This proposed stochastic structure for COPRAS is a practical and powerful tool that strengthens the decision.

Suggested Citation

  • Yelda Ayrim & Kumru Didem Atalay & Gülin Feryal Can, 2018. "A New Stochastic MCDM Approach Based on COPRAS," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 857-882, May.
    • Handle: RePEc:wsi:ijitdm:v:17:y:2018:i:03:n:s0219622018500116
    DOI: 10.1142/S0219622018500116
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    3. Ediz Atmaca & Esra Aktaş & Hafsa Nur Öztürk, 2023. "Evaluated Post-Disaster and Emergency Assembly Areas Using Multi-Criteria Decision-Making Techniques: A Case Study of Turkey," Sustainability, MDPI, vol. 15(10), pages 1-26, May.
    4. Suo, Weilan & Wang, Lin & Li, Jianping, 2021. "Probabilistic risk assessment for interdependent critical infrastructures: A scenario-driven dynamic stochastic model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

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