New extension of ordinal priority approach for multiple attribute decision-making problems: design and analysis

Abstract

The selection and assessment process of appropriate robots became a more complex and complicated task due to various available alternatives and conflicting attributes which must take into consideration. Also, uncertainty which exists usually in the selection process is an unavoidable component that needs to be thoughtfully measured and traditional multi-attribute decision-making approaches failed to deal precisely with it. Since almost all decisions originate from subjective ordinal preferences, handling uncertainty using linguistic variables is also not enough. Thus, the objective of the current study is to present a new extended ordinal priority approach in the neutrosophic environment for the first time to select an appropriate robot. Since neutrosophic is one of the most effective and accommodating tools for handling uncertainty, thus, this method goes to transform linguistic information into triangular neutrosophic numbers using a new presented scale. This scale was used to determine the importance degree of attributes and alternatives regarding experts' opinions. Also, the score function of the triangular neutrosophic number is used for prioritizing attributes and alternatives. The experts in our proposed method have the same degree of importance, since each expert is a person with special skills and knowledge representing mastery of a particular subject. To measure the applicability and efficiency of the proposed approach, an experimental case study has been established for the robot selection problem of a new pharmaceutical city in Egypt for the first time. The source of data in this case study is experts, interviews, and questionnaires. Also, sensitivity and comparative analysis are further made for verifying the power of the proposed approach. The outcome of this study shows that the suggested approach for robot selection is quite helpful and has a great performance under uncertainty over classical and fuzzy ordinal priority approaches. Also, the suggested approach is less consumption of time and simpler than the fuzzy ordinal priority approach. Therefore, we recommend firms and governments to apply it for increasing product quality, hence the profitability of manufacturing industries and decrease needless costs.

A grey ordinal priority approach for healthcare waste disposal location selection

“…Since the last few years, the researchers have endeavoured to explore its capability in solving diverse MCDM problems, like selection of healthcare supplier (Quartey-Papafio et al ., 2021), construction sub-contractor (Mahmoudi and Javed, 2022), project portfolio (Mahmoudi et al ., 2022a), transportation planning strategy (Pamucar et al ., 2022), road maintenance strategy (Bouraima et al ., 2022), distributed ledger technology (Sadeghi et al ., 2022a) and so on. Recently, it has also been successfully combined with TOPSIS for project selection (Mahmoudi et al ., 2021a), and shortlising of automotive parts suppliers (Bah and Tulkinov, 2022); data envelopment analysis (DEA) for supplier performance assessment (Mahmoudi et al ., 2022b); FST for selection of resilient suppliers selection (Mahmoudi et al ., 2022c), blockchain technology selection in construction organizations (Sadeghi et al ., 2022b) and appraising construction suppliers (Mahmoudi et al ., 2022d); neutrosophic fuzzy set for industrial robot selection (Abdel-Basset et al ., 2022); rough set theory for sustainable mining (Deveci et al ., 2022); and grey system theory to evaluate low-carbon sustainable technologies in agriculture (Shajedul, 2021), sustainable supplier selection for construction megaprojects (Mahmoudi et al ., 2021b) and identification of barriers to electric vehicle adoption (Candra, 2022).…”

Probabilistic Approach to Multi-Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach

“…Ataei et al (2020) proposed the OPA and compared it with six other models; AHP, BWM, TOPSIS, VIKOR, PROMETHEE, and QUALIFLEX (see the last row of Table 1 for full names). Their results, and those of succeeding studies (Abdel-Basset et al, 2022;Pamucar et al, 2022;Quartey-Papafio et al, 2021), revealed that the methodology of OPA enjoys several benefits compared with other models. For instance, it has been shown that the OPA does not require a pairwise comparison matrix, normalization of input, and averaging methods for aggregating experts' opinions.…”

Evaluation of Barriers to Electric Vehicle Adoption in Indonesia through Grey Ordinal Priority Approach

“…Pamucar et al (2022) also extended OPA in fuzzy environment to prioritize transport planning strategies. Abdel-Basset et al (2022) extended OPA under neutrosophic environment for evaluation of robots.…”