A general electroelastic analysis of piezoelectric shells based on levy-type solution and eigenvalue-eigenvector method

Qi, Ji; Teng, Ran; Ali, H. Elhosiny; Arefi, Mohammad

doi:10.1016/j.heliyon.2023.e17634

Cited by 2 publications

(1 citation statement)

References 56 publications

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“…The collaborative function-based ranking method that will be used is MCDM-AHP [19], [20] which functions as optimal weighting through optimal eigenvectors, while the ELECTRE method functions as a ranking process for the final decision of the vendor selection process. The MCDM-AHP method has been proven in other research to act as a stage for determining multi-criteria weights [21], [22] based on obtaining eigenvector values [23], [24], through questionnaire instrumentation to provide a comparative weight value for each criterion which is compared objectively. These entries came from 19 respondents through selected vendors who have long carried out business transactions in large capacities, so they can be said to be experts as entities in handling supply chain problems.…”

Section: Introductionmentioning

confidence: 99%

MCDM-AHP and ELECTRE collaboration apps for the best vendor selection technique

Akmaludin,

Samudi,

Baidawi

et al. 2024

Bulletin EEI

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Vendor selection techniques are very important to maintain supply chain services, optimal service creates strong consistency in maintaining the continuity of supply chain business processes. The aim of this research is to provide an objective and consistent understanding of the best techniques in vendor selection which are implemented openly through the collaboration of multi-criteria decision making-analytic hierarchy process (MCDM-AHP) and ELECTRE. Empirical studies show how this approach is able to provide optimal decision-making support for the vendor selection process. Eight criteria are required which have contradictory meanings in their apps. These criteria include quality of goods (QG), payment methods (PMs), payment terms (PTs), minimum transactions (MTs), discounts (DS), delivery times (DTs), inventory (IN), and service (SV). The comparison importance value of the criteria is used as a measure of weighting the criteria through two testing approaches, namely mathematical algebra matrices and expert choice apps, through accurately assessing the optimal eigenvector from the two test approaches. Decision making support was carried out by comparison using 342 preference matrices which were developed into concordance and discordance matrices, the elimination process with threshold matrices found that the ranking results of four vendors were ranked first as worthy of being a selection priority and fifteen other vendors were ranked below.

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