Understanding the core determinants of bunker supply vessel selection for maritime industry: an integrated fuzzy-AHP and fuzzy-TOPSIS approach

Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain

The paper evaluates the reliability of software systems using the multi-criteria decision-making (MCDM) approaches. In this paper, object-oriented software systems are evaluated using the analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS). The selection criteria are determined on the basis of ISO/IEC 25010 quality model. The approaches evaluate and select the most reliable object-oriented software system considering the fuzzy nature of decision-making process. The work is different in nature and easy in comparison to the other reliability evaluation approaches which can be explored according to the needs of an individual from various paradigms of software industry.

Rainfall forecasting is crucial for disaster mitigation, agriculture, and water resource management. However, due to the dynamic nature of weather patterns, predicting rainfall remains a complex challenge. Various meteorological factors influence rainfall, necessitating an effective selection process to identify the most significant parameters. This study introduces a novel approach for parameter selection in rainfall forecasting by integrating two Multi-Criteria Decision-Making (MCDM) techniques: Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). The proposed method prioritizes key meteorological factors that have the greatest impact on occurrence of rainfall and enhancing forecasting precision. The selected parameters contribute to improving rainfall prediction accuracy, reducing errors, and providing a reliable foundation for advanced forecasting models.

A novel fuzzy group decision-making approach based on CCSD method for thermal insulation board selection problem: A case study

PurposeThe purpose of this paper is to introduce a quantitative method for assisting contractors to select appropriate projects for bidding by considering multiple attributes and integrating decision group member opinions.Design/methodology/approachThe fuzzy technique for order preference by similarity to ideal solution (TOPSIS) method is used to help contractors make decision on project selection and the linguistic terms are defined for representing the triangular fuzzy numbers for ratings of alternatives and weights of criteria.FindingsThe selection of appropriate projects for bidding is a multiple attribute group decision‐making exercise. In a real decision process, there are many uncertainties and ambiguities, and time limitations mean that decision makers cannot always make precise judgments. The numerical example demonstrates that the fuzzy TOPSIS approach can be used to simulate the decision process in project selection, and the results provide contractors with valuable insight into the project selection problem.Originality/valueSelecting appropriate projects for bidding is to use a contractor's limited resources more efficiently and increase the probability of winning contracts. Therefore, there is a need for a quantitative method to help contractors make better decision on project selection. That leads to the formulation of this paper. The fuzzy TOPSIS method can assist contractors to make better decisions in bidding.

Shipping logistics is one of the very important criteria which can directly and indirectly affect the economy and GDP of any country. Shipping logistics depends on various factors which have been addressed by several authors in their previous studies. Studies in this literature are focused on selecting the most impactful factors among all the criteria. Methods used in this literature are fuzzy Analytical hierarchy process (AHP) and fuzzy Technique for order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria decision analysis. These methods also helped in this literature to develop a new hybrid method “fuzzy TOPSIS AHP”. There have been no studies involving maritime logistics with comparative analysis of multi-criteria decision making i.e., fuzzy AHP and fuzzy TOPSIS AHP. The literature involved large number of expert opinions on the factor prioritization of maritime logistics. Factors selected for prioritization are Environmental Sustainability, Supply and Demand, Operations and Port Selection. However, the research showed that the comparative analysis of the results was quite opposite to one another and proposed a new way for researchers to use the hybrid method of fuzzy TOPSIS AHP method in future research. The study aimed to improve the existing maritime model which can help professionals to get connected with the maritime logistics firms. The study also aims to contribute this model for researchers in their study related to maritime logistics.

This study aims to find out the strategic priorities of the technical factors to have sustainable low carbon industry. For this purpose, a hybrid multi-criteria decision-making (MCDM) is proposed that contains three different stages. First, the economic criteria required for sustainable development and the technical needs of the low carbon industry are defined by making a comprehensive literature review. After that, economic criteria are weighted by using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) methodology. Finally, technical factors are ranked with the help of the fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach. Moreover, another analysis is also performed by considering fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to evaluate the consistency of the analysis results. The main motivation of this study is to define the primary technical factors to minimize carbon emission problem by proposing a hybrid MCDM model. The findings indicate that research and development for renewable sources has the greatest importance for low-carbon industry. In addition, the analysis results of fuzzy TOPSIS and fuzzy VIKOR are quite similar. This situation demonstrates the consistency and coherency of the ranking results. Hence, it is recommended that countries should mainly give importance to the research and development investments so that the costs of renewable energy problems can be minimized. This situation can attract the attentions of the companies to invest in these projects. In this way, it will be possible to use a cleaner energy in industrial production.

Modern industrial safety alludes to the administration of the multitude of activities and occasions inside an industry to minimise the hazards, risks, accidents or near-misses. This study contains the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) analysis for the factors affecting the industrial safety. The Fuzzy TOPSIS analysis has been done in order to prioritise the factors affecting the industrial safety and to find out which of them are the most vulnerable and need most of our attention. Fuzzy TOPSIS is a technique which is used in a scenario where performance values in decision matrix are not crisp numeric values but instead they are linguistic terms which are given by the decision makers.

Summary. Performance of a faculty is vital both for students and school, and must be measured and evaluated for positive reinforcement to faculty. Faculty performance evaluation problem is a difficult and sensitive issue which has quantitative and qualitative aspects, complexity and imprecision. In literature many different approaches are proposed in order to evaluate faculty performance. To deal with imprecision and vagueness of evaluation measures, fuzzy multi-attribute evaluation techniques can be used. In this paper, a comprehensive hierarchical evaluation model with many main and sub-attributes is constructed and a new algorithm for fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) that enables taking into account the hierarchy in the evaluation model is proposed. The obtained results from this new fuzzy TOPSIS approach are compared with fuzzy Analytic Hierarchy Process (AHP) on an application in an engineering department of a university and some sensitivity analyses are presented.

Application of modified TOPSIS technique in deciding optimal combination for bio-degradable composite

The tribo-performance of nanoclay and multi-walled carbon nanotube (MWNT) filled and graphite lubricated phenolic composites, reinforced with a combination of lapinus and kevlar fibers, have been evaluated on a Kraus friction testing machine. The combined fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) approach, taking into account performance defining attributes (PDAs) such as friction performance, wear, friction-fade, friction-recovery, stability coefficient, variability coefficient, friction fluctuations and temperature rise of the disc, was used for the performance assessment of fabricated friction composite materials. The weight of different PDAs were evaluated by FAHP; μ-performance (0.144, 0.255, 0.435), wear (0.144, 0.255, 0.435), fade-% (0.073, 0.15, 0.307), recovery-% (0.063, 0.126, 0.268), stability coefficient (0.037, 0.075, 0.156), variability coefficient (0.032, 0.063, 0.136), frictional fluctuations (0.023, 0.037, 0.069), and DTR (0.023, 0.037, 0.069) respectively. FTOPSIS was employed to determine the optimal ranking of the friction composite materials as NC-7>NC-8>NC-6>NC-5>NC-3>NC-4>NC-2>NC-1. The alternative with kevlar: lapinus, 2.5:27.5 wt-% and graphite: nanoclay: carbon nanotube, 2.25:2.75 wt-% exhibits the optimal properties.

PurposeThe purpose of this paper is to explore the various disposition alternatives and to develop a framework for the optimal disposition decisions in reverse logistics.Design/methodology/approachIn reverse logistics, once the products are collected and inspected, decision is to be taken regarding their disposition for reuse, re-manufacture or recycle or other possible alternatives. A combination of analytical hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) approach is proposed for the selection of best disposition alternative based on criteria economic benefits, environmental benefits, corporate social responsibility, stakeholder’s needs and reverse logistics resources.FindingsA case of electronics firm was illustrated for the demonstration of the approach for the disposition of mobile phones. Returned mobile phones must be disposed for repairing or reuse in current business scenario, if possible. Otherwise, the firm may prefer to recycle them rather than dispose or remanufacture.Research limitations/implicationsThe study is limited to mobile manufacturing firm. Also, these findings may vary depending on the sector and products. Further, empirical studies and case studies can be carried out to validate the findings.Practical implicationsThe proposed framework provides useful tool to the practitioners and researchers in decision-making for disposition in reverse logistics.Originality/valueVery few studies related to disposition decisions in reverse logistics were found in the previous research literature review. The study will add value to the very limited research on reverse logistics disposition. Also, the AHP-Fuzzy TOPSIS approach is first time being used for the disposition decisions in reverse logistics.

With the globalization of online shopping, deterioration of the ecological environment and the increasing pressure of urban transportation, a novel logistics service mode—joint distribution (JD)—was developed. Selecting the optimal partner combination is important to ensure the joint distribution alliance (JDA) is sustainable and stable, taking into consideration conflicting criteria. In this paper, we present an integrated fuzzy entropy weight, fuzzy analytic hierarchy process (fuzzy EW-AHP) and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) approach to select the optimal partner combination of JDA. A three-phase approach is proposed. In the first phase, we identify partner combination evaluation criteria using an economy-society-environment-flexibility (ESEF) framework from a perspective that considers sustainability. In the second phase, the criteria weights and criteria combination performance of different partner combinations were calculated by using an integrated fuzzy EW-AHP approach considering the objective and subjective factors of experts. In the third phase, the JDA partner combinations are ranked by employing fuzzy TOPSIS approach. The sensitivity analysis is considered for the optimal partner combination. Taking JDA in Chongqing for example, the results indicate the alternative partner combination 3 (PC3) is always ranked first no matter how the criteria weights change. It is effective and robust to apply the integrated fuzzy EW-AHP and TOPSIS approach to the partner selection of JDA.

Bioprinting has been applied to fabricate biomedical parts such as skin, scaffolds, tissues, and muscles. However, most previous studies in this field compared the advantages and/or disadvantages of a bioprinter subjectively. A systematic and objective method for comparing various bioprinters, so as to recommend the most suitable one to a decision maker, is lacking. To address this issue, a fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) approach is proposed in this study. In the proposed FAHP-FTOPSIS approach, FAHP is applied to derive the fuzzy weights of factors critical to the suitability of a bioprinter, based on a decision maker’s subjective judgments. Subsequently, the derived fuzzy weights are fed into the FTOPSIS approach to evaluate the overall performance of a bioprinter. The FAHP-FTOPSIS approach has been successfully applied to the case of making a choice from nine bioprinters. Parametric analyses have also been conducted to show the robustness of the proposed methodology.

A FAHP-FTOPSIS approach for choosing mid-term occupational healthcare measures amid the COVID-19 pandemic