Design concept evaluation based on rough number and information entropy theory

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes

A weighted rough set based fuzzy axiomatic design approach for the selection of AM processes

Additive manufacturing (AM) or 3D printing, as an enabling technology for mass customization or personalization, has been developed rapidly in recent years. Various design tools, materials, machines and service bureaus can be found in the market. Clearly, the choices are abundant, but users can be easily confused as to which AM process they should use. This paper first reviews the existing multi-attribute decision-making methods for AM process selection and assesses their suitability with regard to two aspects, preference rating flexibility and performance evaluation objectivity. We propose that an approach that is capable of handling incomplete attribute information and objective assessment within inherent data has advantages over other approaches. Based on this proposition, this paper proposes a weighted preference graph method for personalized preference evaluation and a rough set based fuzzy axiomatic design approach for performance evaluation and the selection of appropriate AM processes. An example based on the previous research work of AM machine selection is given to validate its robustness for the priori articulation of AM process selection decision support

Using fuzzy PROMETHEE to select countries for developmental Aid

Wealthy nations continue to demonstrate their unwavering support to improving conditions and the general well-being of poor countries in spite of the recent economic crises. However, as developmental aid relatively shrinks, both Aid donors and recipient countries have shown keen interest in methodologies used in evaluating developmental assistance programs. Evaluation of aid programs is seen as a complex task mainly because of the several non-aid factors that tend to affect overall outcomes. Adding to the complexity are the subjective sets of criteria used in Aid evaluations programs. This paper proposes a two stage framework of fuzzy TOPSIS and sensitivity analysis to demonstrate how aid-recipient countries can be evaluated to deepen transparency, fairness, value for money and sustainability of such aid programs. Using the Organisation for Economic Co-operation and Development (OECD) set of subjective criteria for evaluating aid programs; a numerical examplepre-defined by linguistic terms parameterized by triangular fuzzy numbers is provided to evaluate aid programs. Fuzzy PROMETHEE is used in the first stage to evaluate and rank aid-recipients followed by a comparative analysis with Fuzzy VIKOR and Fuzzy TOPSIS to ascertain an accurateness of the method used. A sensitivity analysis is further added that anticipates possible influences from lobbyists and examines the effect of that bias in expert ratings on the evaluation process. The result shows a framework that can be employed in evaluating aid effectiveness of recipient-countries

An overview of multi-criteria decision-making methods in dealing with sustainable energy development issues

© 2018 by the authors. The measurement of sustainability is actively used today as one of the main preventative instruments in order to reduce the decline of the environment. Sustainable decision-making in solving energy issues can be supported and contradictory effects can be evaluated by scientific achievements of multi-criteria decision-making (MCDM) techniques. The main goal of this paper is to overview the application of decision-making methods in dealing with sustainable energy development issues. In this study, 105 published papers from the Web of Science Core Collection (WSCC) database are selected and reviewed, from 2004 to 2017, related to energy sustainability issues and MCDM methods. All the selected papers were categorized into 9 fields by the application area and into 10 fields by the used method. After the categorization of the scientific articles and detailed analysis, SWOT analysis of MCDM approaches in dealing with sustainable energy development issues is provided. The widespread application and use of MCDM methods confirm that MCDM methods can help decision-makers in solving energy sustainability problems and are highly popular and used in practice

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use

A novel sorting method topsis-sort: an applicaiton for tehran environmental quality evaluation

Many real-life problems are multi-objective by nature that requires evaluation of more than one criterion, therefore MCDM has become an important issue. In recent years, many MCDM methods have been developed; the existing approaches have been improved and extended. Multi criteria decision analysis has been regarded as a suitable set of methods to perform sustainability evaluations. Among numerous MCDM methods developed to solve real-life decision problems, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily in diverse application areas. In this paper, a novel sorting method (TOPSIS-Sort) based on the classic TOPSIS method is presented. In the TOPSIS-Sort approach an outranking relation is used for sorting purposes. The proposed approach uses characteristic profiles for defining the classes and outranking relation as the preference model. Application of the proposed approach is demonstrated by classifying 22 districts of Tehran into five classes (but none of the districts fits into Classes 4 and 5), representing areas with different levels of environmental quality. An analysis and assessment of the environmental conditions in Tehran helps to identify the districts with the poor environmental quality. Priority should be given to these areas to maintain and improve the quality of environment. The results obtained by the TOPSIS-Sort give credence to its success, because the results of sorting con firm our and specialists’ evaluation of the districts. This research provides appropriate results with respect to the development of sorting models in the form of outranking relations. The model, proposed by this study, is applicable to the other outranking methods such as ELECTRE, PROMETHEE, etc

A FBWM-PROMETHEE approach for industrial robot selection

Industrial engineering; Multidisciplinary design optimization; Manufacturing engineering; Technology management; Operations management; Industry management; Business management; Industrialization; Industrial robots; Fuzzy best-worst method; PROMETHEE; MCDM; Robot selection; Criteria.publishersversionpublishe

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology