Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process

The proposed system illustrates that logic fuzzy can be used to aid management in assessing a supplier's environmental performance in the supplier selection process. A user-centred hierarchical system employing scalable fuzzy membership functions implement human priorities in the supplier selection process, with particular focus on a supplier's environmental performance. Traditionally, when evaluating supplier performance, companies have considered criteria such as price, quality, flexibility, etc. These criteria are of varying importance to individual companies pertaining to their own specific objectives. However, with environmental pressures increasing, many companies have begun to give more attention to environmental issues and, in particular, to their suppliers’ environmental performance. The framework presented here was developed to introduce efficiently environmental criteria into the existing supplier selection process and to reflect on its relevant importance to individual companies. The system presented attempts to simulate the human preference given to particular supplier selection criteria with particular focus on environmental issues when considering supplier selection. The system considers environmental data from multiple aspects of a suppliers business, and based on the relevant impact this will have on a Buying Organization, a decision is reached on the suitability of the supplier. This enables a particular supplier's strengths and weaknesses to be considered as well as considering their significance and relevance to the Buying OrganizationPeer reviewe

Analysis of Green Computing Strategy in University: Analytic Network Process (ANP) Approach

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis do not provide an analytical means to determine the importance of the identified factors of green computing strategy and implementation. Although the SWOT analysis successfully explores the factors, individual factors are usually described very generally. For this reason, SWOT analysis possesses deficiencies in the measurement and evaluation of green computing steps. Even though the analytic hierarchy process (AHP) technique eliminates these deficiencies, it does not allow for measuring the possible dependencies among the individual factors. The AHP method assumes that the green computing factors presented in the hierarchical structure are independent; however, this assumption may be inappropriate in light of certain situation. Therefore, it is important to utilize a form of SWOT analysis that calculates and takes into account the possible dependency among the factors. This paper demonstrates a process for quantitative SWOT analysis of green computing implementation that can be performed even when there is dependence among strategic factors. The proposed algorithm uses the analytic network process (ANP), which allows measurement of the dependency among the green computing implementation factors, as well as AHP, which is based on the independence between the factors. There are four alternatives: campus awareness program, computer procurement, increase in heat removal requirement, and increase in equipment power density for improving the implementation of green computing in campus. Dependency among the SWOT factors is observed to effect the strategic and sub-factor weights, as well as to change the strategy priorities. Based on ANC method, the best alternative for this implementation is computer procurement

Market segment evaluation and selection based on application of fuzzy AHP and COPRAS-G methods

Market segment evaluation and selection is one of the critical marketing problems of all companies. This paper presents a novel approach which integrates fuzzy analytic hierarchy process (FAHP) and COPRAS-G method for market segment evaluation and selection. Fuzzy AHP is used to calculate the weight of each criterion, and COPRAS-G method is proposed to prioritize market segments from the best to the worst ones. The application of fuzzy set theory allows incorporating the vague and imprecise linguistic terms into the decision process. This study can be used as a pattern for market segment selection and future researches. A case study on a chair manufacturing company is put forward to illustrate the performance of the proposed methodology. First published online: 14 Sep 201

Ranking of manufacturers of mechanical parts based on a fuzzy multi-criteria decision making method: A case study in Iran National Steel Industrial Group

Considering multiple criteria in evaluating manufacturers, high number of parts, orders and manufacturers for supplying parts of machinery and equipment, selecting the right manufacturer is a serious problem in steel rolling and production factories. The use of Multi-Criteria and methods in decision-making plays an important role in the selection speed and accuracy. Because of multiple criteria in evaluating manufacturers, selecting a limited and effective number of manufacturers seems difficult, so this study aimed to rank potential suppliers in order to identify the best supplier. Decisions in the outsourcing of mechanical parts are made based on multi-criteria methods and grouped decisions. So, this article proposes a method based on the grouped fuzzy decision-making approach in order to evaluate and rank the most suitable suppliers for outsourcing activities in Iran National Steel Industrial Group. Using the proposed method, experts presented their opinions in linguistic words, a range of numbers, deterministic or fuzzy numbers. Then each supplier was ranked based on the model criteria. On this basis, the most effective criteria in selecting companies were also identified

A Fuzzy Based Approach for New Product Concept Evaluation and Selection

Product developers make many decisions during the early stages of product development which have a profound impact on the final cost of the product. These decisions include selecting a product concept that best meet customer needs.  Product concept selection involves using the collective knowledge of many experts who possess different backgrounds and expertise in various fields to evaluate a set of product concepts developed to meet certain customer needs. This paper proposes a concept evaluation and selection methodology capable of capturing the fuzziness and vagueness impeded in concept evaluation. The proposed methodology integrates the Weighted Concept Selection Matrix with the Analytical Hierarchal Process (AHP) under a Fuzzy environment. The developed methodology has the capability of capturing the fuzziness and vagueness in the concept evaluators’ ratings. The methodology consists of eight steps that begins with retrieving the product concepts, developing the evaluation criteria and selecting the evaluators, and ends up by choosing the best concept. The criteria are prioritized and assigned fuzzy weights according to their importance with respect to the nature of the product and based on the capabilities of the manufacturing company.  Furthermore, the evaluators are prioritized and assigned fuzzy weights with respect to the criteria based on their different backgrounds. These weights are aggregated with the concepts’ fuzzy rating done by the evaluators in order to compute a final score for each concept. The usage of the methodology is verified and tested by using an illustrative example. Keywords: Product Design, Fuzzy systems, Multi-criteria Decision Making, Analytical Hierarchal Proces