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Large-scale multiple criteria decision-making with missing values: project selection through TOPSIS-OPA

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Abstract

Nowadays, with the development of information management infrastructures in organizations and the improvement of the data storage process, managers are looking for appropriate decision-making methods based on large volumes of data. Therefore, it is crucial to choose the right approach to make the right decisions based on the volume of available data. The present study seeks to provide a comprehensive framework for the decision-making process using big data, even when it is incomplete. The framework of multiple criteria decision making (MCDM) consists of criteria and alternatives, whereas in real-world cases, decision-makers may face several criteria and alternatives. In this study, the Principal Component Analysis (PCA) approach was selected for the criteria clustering. Later, the K-means algorithm is used to cluster the alternatives, which estimates the optimal number of clusters using the Elbow method. The Fuzzy TOPSIS (TOPSIS-F) and Ordinal Priority Approach (OPA) have been used to rank clusters. Ultimately, the best alternative in the top cluster has been identified with the aid of the OPA, which has a unique function to solve MCDM problems with incomplete data. For evaluating the performance of the proposed approach, first, a pilot testing has been executed on a real-world case, and then a practical study was conducted at a refinery equipment manufacturing company with a project-oriented organizational structure. The approach is flexible, interactive, intelligent, and integrative, and significantly reduces the time and computation costs for the decision-makers. The results confirmed the soundness of the proposed approach, which can be used by managers of different companies with confidence.

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Acknowledgements

This study was supported by the National Natural Science Foundation of China under Grant No. NSFC-71771052. The work presented in this paper corresponds to the doctoral dissertation of the first author at the Southeast University, China. More information regarding the ordinal priority approach (OPA) can be found at www.ordinalpriorityapproach.com. The authors would like to thank Mr Mostafa Parvizi from FSK company for his support and cooperation.

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Authors and Affiliations

  1. Department of Construction and Real Estate, School of Civil Engineering, Southeast University, Nanjing, 210096, China

    Amin Mahmoudi, Xiaopeng Deng & Jingfeng Yuan

  2. School of Business, Nanjing University of Information Science and Technology, Nanjing, 210044, People’s Republic of China

    Saad Ahmed Javed

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  1. Amin Mahmoudi
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  2. Xiaopeng Deng
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  3. Saad Ahmed Javed
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  4. Jingfeng Yuan
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Correspondence to Xiaopeng Deng.

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Mahmoudi, A., Deng, X., Javed, S.A. et al. Large-scale multiple criteria decision-making with missing values: project selection through TOPSIS-OPA. J Ambient Intell Human Comput 12, 9341–9362 (2021). https://doi.org/10.1007/s12652-020-02649-w

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