A novel integrated large-scale group MCDM model under fuzzy environment for selection of reach stacker in a container terminal

An integrated fuzzy MCDM model for prioritizing strategies for successful implementation and operation of the bus rapid transit system

The selection and prioritization of suitable strategies to address the challenges to the successful operation and implementation of the bus rapid transit (BRT) system is a common problem faced by practitioners and decision-makers. Recent research has widely discussed the issue, but such assessments have remained limited in the city of Dar es Salaam, Tanzania context, where there are mobility difficulties. The present study addresses this research gap and identifies the most critical challenges to BRT implementation and operation, and recommends the most appropriate strategy for overcoming them. Seven strategies are defined. To prioritize these strategies, five criteria are determined. An integrated multi-criteria decision-making model is introduced. Improved Fuzzy Step-Wise Weight Assessment Ratio Analysis based on the Bonferroni operator was used to determine the importance of the criteria. Measurement of alternatives and ranking according to compromise solution was applied to assess and rank the strategies. The results indicate that "frequent flooding at the Jangwani bridge bus terminal" and "long waiting time at bus stops" are the most critical challenges while the fourth alternative "strengthening the operation and management" is the appropriate strategy to be implemented for successful operation and implementation of the BRT system. After that, a five-phase sensitivity analysis is performed to observe the robustness of the proposed approach. The results indicate the flexibility and applicability of the proposed approach can address real-life problems. The proposed methodology in this work can be instrumental in assisting mass transit operators with the successful implementation and operation of the BRT system.

Analysis and Applications of Bonferroni Mean Operators and TOPSIS Method in Complete Cubic Intuitionistic Complex Fuzzy Information Systems

This article manages vagueness, asymmetric data, and risk demonstrated in awkward information. The ambiguity is handled with the help of possibility and strategic decision-making theory. A MADM (multi-attribute decision-making) tool, the sub-part of the strategic decision theory, plays an important role in the circumstances of fuzzy data. The major influence of this analysis is to initiate the mathematical ideology of cubic intuitionistic complex fuzzy (CICF) information and its well-known properties such as algebraic laws, score values, and accuracy values. It is also to determine various inequalities for finding the relation between any two CICF numbers (CICFNs). Further, we know that the Bonferroni mean (BM) operator is more generalized than the simple averaging/geometric aggregation operators due to parameters involved in the mathematical form of BM operators. Keeping the supremacy and consistency of BM operators, the idea of CICF Bonferroni mean (CICFBM) and CICF weighted BM (CICFWBM) operators are diagnosed. We try to describe their well-known results and properties such as idempotency, monotonicity, commutativity, and boundedness with various specific cases. Further, we investigate three different sorts of decision-making procedures such as MADM tool, TOPSIS (Technique for order of preference by similarity to ideal solution) method using similarity measures, and TOPSIS method using aggregation operators to enhance the quality of the decision-making process. This analysis expressed how to make decisions when there is asymmetric data about companies. Finally, we compute the comparative analysis of the diagnostic approaches with various existing theories to demonstrate the feasibility and flexibility of the exposed work to try to illustrate with the help of geometrical expressions.

Pallet truck selection with MEREC and WISP-S methods

Background: The article presents an MCDM model based on the MEREC and WISPS methods for pallet truck selection. Purpose: The main purpose of the study was to apply a new MCDM model for pallet truck selection in the textile workshop. Study design/methodology/approach: This article presents a simplified adoption of the Simple Weighted Sum Product (WISP) method, the Simplified WISP (WISP-S) method. The proposed method has fewer computation steps than the regular WISP method. In addition, this study proposes a new hybrid MCDM model in the literature by combining the MEREC method and the WISPS method. Finding/conclusions: The obtained results can be achieved in a shorter time compared to regular WISP. The application of the new method is considered in this study. In order to check whether the WISPS method achieves accurate results, the results of the WISPS method and the results of the ROV and WASPAS methods were compared. As a result of the comparison of the results of the methods, it was observed that the WISPS method achieved accurate results. Limitations/future research: As a direction for future research, other MCDM models can be applied for solving the same problem. When it comes to the limitations of the proposed model, it can be mentioned that the MCDM model is based on the use of crisp numbers.