Dependability assessment of supplier performance based on the fuzzy sets theory

In the literature, considerable attention has been given to the role of suppliers, thus companies have been increasingly considering better supplier selection approaches in order to attain the competitive advantage in the demanding markets. The aim of this study is to provide an effective tool for decision makers (DMs) to help them with evaluation and prioritization of current suppliers. Moreover, the supplier prioritization is inherently multicriteria decision-making problem (MCDM), with involved high degree of fuzziness. Hence, this paper introduces fuzzy decision-making model where dependability assessment of the suppliers could be done based on the fuzzy set theory and max-min composition. Furthermore, in order to determine supplier dependability, the typical influence indicators: Production facilities and capacities (PFC), Delivery (D) and Service (S), were analysed in an illustrative example, where proposed model used triangular fuzzy numbers (TFN) to establish linguistic description of these three indicators. At the practical level, the results and findings of this paper provide decision makers with a complete picture of those suppliers that have the highest dependability performance in their supplier network

Multicriteria Model for the Choice of Best Battery Provider

The choice of suppliers is a matter of great importance in organizations. The cost, quality and delivery time provided to customers may depend to a large extent on this decision. This paper, therefore, describes a model applicable to a real organization, using multicriteria decision techniques to choose the best supplier of batteries. In order to establish concordance and discordance thresholds the values provided by the decision-maker of the company will be compared with those obtained by the fuzzy Analytic Hierarchy Process. Both valuations of the thresholds will be applied in the ELECTRE II technique

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Managing Interacting Criteria: Application to Environmental Evaluation Practices

The need for organizations to evaluate their environmental practices has been recently increasing. This fact has led to the development of many approaches to appraise such practices. In this paper, a novel decision model to evaluate company’s environmental practices is proposed to improve traditional evaluation process in different facets. Firstly, different reviewers’ collectives related to the company’s activity are taken into account in the process to increase company internal efficiency and external legitimacy. Secondly, following the standard ISO 14031, two general categories of environmental performance indicators, management and operational, are considered. Thirdly, since the assumption of independence among environmental indicators is rarely verified in environmental context, an aggregation operator to bear in mind the relationship among such indicators in the evaluation results is proposed. Finally, this new model integrates quantitative and qualitative information with different scales using a multi-granular linguistic model that allows to adapt diverse evaluation scales according to appraisers’ knowledge

Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters

[EN] International trade in food knows no borders, hence the need for prevention systems to avoid the consumption of products that are harmful to health. This paper proposes the use of multicriteria risk prevention tools that consider the socioeconomic and institutional conditions of food exporters. We propose the use of three decision-making methods-Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), Elimination et Choix Traduisant la Realite (ELECTRE), and Cross-Efficiency (CE)-to establish a ranking of countries that export cereals to the European Union, based on structural criteria related to the detection of potential associated risks (notifications, food quality, corruption, environmental sustainability in agriculture, and logistics). In addition, the analysis examines whether the wealth and institutional capacity of supplier countries influence their position in the ranking. The research was carried out biannually over the period from 2012-2016, allowing an assessment to be made of the possible stability of the markets. The results reveal that suppliers' rankings based exclusively on aspects related to food risk differ from importers' actual choices determined by micro/macroeconomic features (price, production volume, and economic growth). The rankings obtained by the three proposed methods are not the same, but present certain similarities, with the ability to discern countries according to their level of food risk. The proposed methodology can be applied to support sourcing strategies. In the future, food safety considerations could have increased influence in importing decisions, which would involve further difficulties for low-income countries.Ministry of Science and Innovation (Spain) and European Commission-ERDF. 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Supplier Selection Problem under Z-information

AbstractSupplier selection problem is a very important element of Supply Chain Management systems. The existing works are devoted to solving this problem under deterministic, stochastic, interval-based and fuzzy information. Unfortunately, up today no systematic research on supplier selection under partial reliability of information is proposed. In this paper we suggest new method for solving supplier selection problem under fuzzy and partially reliable information formalized by using Z-numbers. The method is based on determination of Z-number valued ideal and negative ideal solutions. A numerical example is provided to illustrate validity of the proposed approach to supplier selection problem