In this work, a version of the technique for order preference by similarity ideal solution (TOPSIS) with entropic regularization approach is developed for solving the fuzzy multi-objective nonlinear programming (MONLP) problems. Applying the basic principle of compromise of TOPSIS, the fuzzy MONLP problem can be reduced into a fuzzy bi-objective nonlinear programming problem. Moreover, followin...

In this paper, we extend TOPSIS (Technique for Order Preference by Similarity Ideal Solution) for solving Large Scale Multiple Objective Programming problems involving fuzzy parameters. These fuzzy parameters are characterized as fuzzy numbers. For such problems, the α-Pareto optimality is introduced by extending the ordinary Pareto optimality on the basis of the α-Level sets of fuzzy numbers. ...

The Evaluation of eCRM implementation in most of organizations will witness an increase in efficiency, staff satisfaction, and eventually customer satisfaction. The objective of this paper is to apply and compare the analytic hierarchy process (AHP), Fuzzy AHP and Fuzzy Topsis methods to evaluate the Parsian banks’ readiness in ECRM implementation. Primary data have been collected by means of q...

This paper applies fuzzy set theory to evaluate the service quality of online auction. Service quality is a composition of various criteria. Among them many intangible attributes are difficult to measure. This characteristic introduces the obstacles for respondent in replying to the survey. So as to overcome this problem, we invite fuzzy set theory into the measurement of performance. By using ...

A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the f...

A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the f...

Multicriteria decision making ~MCDM! methods can be powerful aids for evaluating patients’ medical information in medical diagnostic systems. Technique ordered preference by similarity to the ideal solution ~TOPSIS! is one of the more widely used MCDM methods in decision support systems. For the purpose of this work, the TOPSIS method is modified into a more suitable form and used for the imple...

Selecting the appropriate manufacturing machine is a very important and complex problem for firms which usually have to deal with both qualitative and quantitative criteria and involve different decision makers whose knowledge is often vague and imprecise. This paper proposes a peer-based modification to intuitionistic fuzzy multi-criteria group decision making with TOPSIS method (peer IF-TOPSI...

This paper presents a fuzzy multiple criteria decision making (FMCDM) problem with the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) based on the new concept of positive and negative ideal solution. Whereas decision making is a process which accuracy of data play major role to select the best alternative, considering decision making problems in fuzzy environments moti...

In hotly competitive international industrial and economic environments, supply chain coordination (SCC) is one of active research topics in production and operation management. In this research work, we present a new consensus-based fuzzy TOPSIS approach for supply chain coordination problem. It is formulated as a multi-criteria group decision making (MCGDM) problem and solved by combining con...