Search results

The purpose of this paper is to develop a method to select the best alternative in a multi‐criteria decision making (MCDM) environment when the decision is taken by a group of members in an uncertain environment.

In this paper, Fuzzy Preference Ranking Organization Method for Enrichment Evaluations (Fuzzy PROMETHEE) technique has been used for MCDM problems. The team of decision makers is constituted to integrate their opinion. The analysis is done using Geometrical Analysis for Interactive Aid (GAIA) plane, available in Decision Lab 2000 software, which provides valuable help in understanding the conflicts among criteria.

The selection of best alternative is done on the basis of generally conflicting criteria. Fuzzy PROMETHEE technique has been proposed and the same is demonstrated using Decision Lab 2000 software. This software can be used for as many criteria as possible and also in a fuzzy environment, where the crisp data for criteria comparison are not available. It is found that the analysis of the results becomes very easy and effective with this software. A case study is conducted for a cement company to select the logistic service providers (LSPs) to demonstrate its ease and effectiveness of use.

The research provides a model to choose the best alternative using Decision Lab 2000 software for Fuzzy PROMETHEE technique. The proposed methodology can be used in a fuzzy environment with ease and effectiveness. In the competitive scenario, this could help the industry in prompt and efficient decision making in MCDM problems.

The purpose of this paper is to prioritize Indian energy sector projects, namely, coal, gas, hydro and solar using fuzzy PROMETHHE (F-PROMETHEE) and Visual PROMETHEE applications and multicriteria decision-making (MCDM) analyses.

The MCDM outranking approach of PROMETHEE under fuzzy environment is used. Four projects of energy sector are selected as alternatives and are compared based on various criteria. These criteria selected on the perspectives of life cycle costing (LCC) analysis and related management approaches for prioritizing projects for effective decision-making (DM). The F-PROMETHEE is described and results are also compared with outranking application in Visual PROMETHEE software based on same set of criteria. For better understanding, the graphical representations of the multicriteria problem are also shown using graphical analysis for interactive aid.

On applying F-PROMETHEE on four energy projects, coal and solar projects outrank high and results shows that coal-based project is preferable and should be considered.

Here F-PROMETHEE and Visual PROMETHEE are used as MCDM techniques. However, few other MCDM techniques such as ELECTRE and EATWOS can be also explored to outrank Indian energy sector projects.

Indian energy sector involves high degree of complexity for effective DM on the front of prioritized investment-related capacity addition through energy projects. Outranking methods like F-PROMETHEE is able to address the criteria to criteria impact on DM support precisely.

The finding can provide information to the government or public sector regarding various possible investment options on energy projects in India.

This paper can be supplement and act as the support for DM in conflicting situations specifically for prioritizing investments on various energy projects, which further can synergize conflicting ideas of various stakeholders of the Indian energy sector.

The purpose of this research paper is to assess efficacy of e-governance implementation, influenced under the Indian-EU (European Union – EU) strategic dialogue. For the same purpose, this study aims to analyse and measure penetration level of information and communication technology (ICT) applications across ten select gross domestic product-dependent sectors (gross domestic product – GDP) in Indian economy.

Multi-criteria decision-making (MCDM) approach of PROMETHEE, using its partial and complete versions in fuzzy environment, is applied. The approach assesses e-governance efficacy in various sectors, which is chosen based on their contribution to GDP, where criteria values are assigned by expert opinions, feedback is received and lessons are learnt from training and initiatives taken under the Digital India programme launched by the Government of India. These criteria related to IT policy implementation, cyber security breaches, IT infrastructure development initiatives in select sectors are identified. Later, sectors outranking results have been highlighted using both fuzzy set theory along with PROMETHEE (F-PROMETHEE) and its visual application.

On applying F-PROMETHEE, studies found that industrial, railways, health and finance and education sectors outrank in their high merit orders. Contrary, outranking shows that agriculture, defence and aerospace sectors should be more open and accessible to adopt ICT applications in order to promote e-governance processes and their implementation to make e-services available to common citizens. For better interpretation of results, graphical analysis for interactive aid is used to present the analyses.

Research study was found useful in the assessment of ICT penetration level in to support Indo-EU relations, where PROMETHEE method is used to outrank sectors alternatives. Criteria are also weighted using fuzzy scale, and the impact of criteria on all alternatives has also been assessed. MCDM framework addresses that subjectivity lies in sectors to implement ICTs bases services. However, few other MCDM frameworks, methods such as COPRAS, GST, GRA, SAW and SWARA, can be used for the same purpose.

Sectors alternative involve high degree of complexity to adopt ICT applications for smooth e-governance and seek effective decision-making for investment prioritization and future development. This study also aims to address cyber security concerns of policymakers. Outranking methods of F-PROMETHEE are able to address the criteria-to-criteria impact and support decision-making in a more precise way.

This study is inspired from the strategic implementation of the framework of the e-Government Action Plan 2016-2020 of the EU. The findings from the paper can provide referential support to the Indian Government and policymakers to support information delivery, implement cyber security policies and various sector developments.

This research study can act as a strong base in the decision-making process in conflicting situations of e-governance in India. This study not only can synergize conflicting ideas of various stakeholders, academicians in the Indian IT-sector but also can act as support to administrators and the policymakers to monitor the status of the India-EU Information Society Dialogue.

The purpose of this paper is to extend the PROMETHEE method under typical hesitant fuzzy information for solving multi-attribute decision-making problem in which there is hesitancy among experts.

Different aggregation and distance functions were developed to deal with HFS. But it is rational that different operators applying in existing methods can produce different results. Also, it is difficult for decision makers to select suitable operators. To address the drawback, this paper develops the PROMETHEE method as an outranking approach to accommodate hesitant fuzzy information. Since the proposed method is constructed on the basis of the pair-wise comparisons, it is independent of the aggregation and distance functions.

To demonstrate the efficiency and accuracy of the proposed method, the authors provide a numerical example and a comparative analysis. The results indicate that outranking-based methods suggest a better ranking than the aggregation- and distance-based methods.

The proposed approach does not consider the hesitant fuzzy linguistic information decision-making problem.

The proposed approach can be applied in many group decision-making problems in which there is hesitancy among experts.

This paper proposes an extension on PROMETHEE method under hesitant fuzzy information, which has not been reported in the existing academic literature.

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.

The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.

The incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.

The designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.

The case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.

Inclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.

The objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.

The need for the thermal insulation of masonry buildings in Algeria is no longer debated. This paper aims to propose an integrated fuzzy multi-criteria decision aid method for the thermal insulation of masonry buildings to rank the thermal insulation solutions.

The proposed method combines the fuzzy analytical hierarchy process with the fuzzy preference ranking organization method for enrichment evaluation.

A case study using the proposed method is detailed in this paper. The building users’ preferences obtained by the fuzzy analytical hierarchy process had a higher level of consistency and accuracy. The case study demonstrates how in a highly uncertain field such as thermal insulation of masonry buildings, the fuzzy preference ranking organization method for enrichment evaluation can prevent the loss of valuable evaluation data and overcome difficulty in integrating linguistic assessments of the thermal insulation alternatives.

The proposed method extends current knowledge by using the fuzzy analytical hierarchy process to consider uncertainties regarding the building users’ preferences, and the fuzzy preference ranking organization method for enrichment evaluation to get a complete ranking of the thermal insulation solutions taking into account the uncertainties related to the alternatives’ evaluations.

In most developing countries riveting, upset forging and punching operations among others are performed using manual hammering technique. The use of the manual method increases production time and reduces efficiency. The use of the manual approach is predominantly due to the high cost of imported automated hammering machines (AHM) which the majority of the end-users are incapable of acquiring. The purpose of this paper, therefore, is to produce an AHM that is affordable using an effective material selection methodology in the design and fabrication process.

The material selection methodology proposed is the fuzzy multi-objective optimisation on the basis of the ratio analysis (MOORA) method. The tool was used to evaluate and determine the optimum material for the major of the components of the AHM from amongst alternative materials while considering several decision criteria. A case study of the shaft was applied to demonstrate the suitability of the proposed technique. The AHM components design is then carried out and machine fabricated and tested to ascertain performance effectiveness.

The result of the fuzzy MOORA evaluation showed that alloy steel is the optimal material for the shaft. The fuzzy MOORA approach was compared with the fuzzy Vlsekriterijumska Optimizacija Ikompromisno Resenje (VIKOR) and fuzzy grey relational analysis (GRA) methods to validate the proposed method. The fuzzy MOORA method produces completely the same result with the fuzzy VIKOR and fuzzy GRA methods. The machine was then designed, constructed and tested and found to be effective for the purpose of the design.

This is significant as no such study has been published by any other researcher to the best of our knowledge in this area.

The food industry is crucial in delivering healthy products for life saving of the society. The identification of key barriers of knowledge management (KM) is desired to enhance the sustainability of the industry. KM has been seen as a part of sustainable development by reducing the bullwhip effect in the entire supply chain. The core objective of the existing research is to prioritize the essential factors of KM adoption in sustainable supply chain (SSC) based on fuzzy analytical hierarchy process (FAHP) method.

In order to fulfill objectives of this study, an extensive review of literature and a questionnaire-based field visits were conducted. A total of five major barriers categories and 22 sub-barriers categories were identified in food sector of Pakistan using experts' inputs. This study employed fuzzy analytical hierarchy process (FAHP).

Managerial barriers, innovation and technological barriers categories are found to be highly prioritized among others. Further, the sensitivity analysis is applied to check the incremental changes of ranked barriers. This prioritization of barriers and incremental changes in them is expected to serve food sector for long-term sustainability and competitive advantage for importers and exporters. Finally, the findings of this research are very helpful for industrial experts, practitioners, consultants and government officials in effectively developing policies regarding KM adoption in line with sustainable goals.

The present work is conducted in the Pakistani context; however, the benchmark model may be tested and applied to other developing countries to compare the outcomes. For further research, the identified barriers may also be evaluated to establish their inter-relationships, using ISM, DEMATEL, ANP, etc. Similarly, the results of this study can also be compared with that of other fuzzy multi-criteria techniques like fuzzy TOPSIS, fuzzy VIKOR, fuzzy ELECTRE, fuzzy PROMETHEE, or fuzzy VIKOR.

This research study can facilitate policymakers, government bodies, stakeholders and supply chain professionals to recognize the key barriers they may encounter in adopting KM practices in their SSC. Additionally, this work helps managers to evaluate the identified barriers by computing their relative importance in adopting KM practices at managerial levels like strategically, tactically and operationally activities in business. This study also facilitates industrial management in formulating policies and action plans in case of implementation, eliminating the barriers in adoption of KM, and SSC successfully.

Few research studies were conducted on KM adoption in industries of China, India, Turkey, Saudi Arabia and Malaysia, but due to workforce diversity these industries have dissimilar views of experts about KM adoption. This study significantly contributed to fill the existing literature gap for prioritization of key barriers against KM implementation in Pakistani context.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.