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Evaluating the performance of activities or organizations by traditional Data Envelopment Analysis (DEA) as efficiency frontier analysis models requires crisp input/output data. However, in real-world problems inputs and outputs are often imprecise. This study develops DEA models using imprecise data represented by fuzzy sets. An important outcome of assessing relative efficiencies within a group of Decision Making Units (DMUs) in fuzzy data envelopment analysis is to determine efficient DMUs. We find efficiency measures with fuzzy inputs and outputs via proposed model. An example using fuzzy data is presented for illustrative purposes. We apply this method in the application to the power generation sector of Iran. Keywords: Fuzzy logic, optimization, data envelopment analysis, power plant, INTRODUCTION Efficiency frontier analysis has been an important approach of evaluating firms' performance in private and public sectors. There have been many efficiency frontier analysis methods reported in the literature. [...]

Abstract: Experimental design technique is a powerful tool that is used in uncertainty cases, when a great amount of data is available. In this paper, effects of different factors on [...]

This paper considers a multi-period and product inventory-routing problem. This model involves two levels, namely, a distributor and several retailers. This problem is modeled with the aim of minimizing bi-objectives, namely, the total cost of the system (including start-up, distribution, and maintenance costs) and risk-based transportation. Products are delivered to retailers by some heterogeneous vehicles with specific capacities through a direct delivery strategy, and inventory shortage is assumed to be impermissible. To validate this new bi-objective model, the ε-constraint method is used to solve problems. Because problems without distribution planning are very complex to solve optimally, the problem considered in this paper is also Non-deterministic Polynomial (NP-hard). Therefore, a nondominated sorting genetic algorithm (NSGA-II) and a multi-objective imperialist competitive algorithm (MOICA) are used and developed to solve a number of test problems. Furthermore, the computational results are compared and the performance of the foregoing algorithms is analyzed. [ABSTRACT FROM AUTHOR]

Byline: A. Azadeh, S.F. Ghaderi, J. Barati Rad Organisations that implement strategic energy management programs undertake a set of activities that, if carried out properly, have the potential to deliver sustained energy savings. One key management opportunity is determining an appropriate level of energy performance for a plant through comparison with similar plants in its industry. Performance-based indicators are one way to enable companies to set energy efficiency targets for manufacturing facilities. This article demonstrates a hybrid approach composed of corrected ordinary least square (COLS), data envelopment analysis (DEA) and principal component analysis (PCA) to analyse energy efficiency (plant-level) for assembly automobile plants that produce passenger cars, light-duty trucks, sport utility vehicles, and vans. Various assembly plants of Toyota, Volkswagen, DaimlerChrysler and Saypa in Japan, USA, Germany and Iran, are considered respectively, as the case of this study. This is the first study which introduces an integrated approach for multi objective energy efficiency problems in auto industries.

Byline: A. Azadeh, S.F. Ghaderi, A. Vazifeh The ever-increasing growth and development of the automotive industry all over the world requires continuous assessment through robust scientific methodologies. This study introduces an integrated model for assessment and analysis of automotive industries on the basis of international and standard indicators. This study, for the first time, evaluates and analyses automotive industries according to a set of standard economic indicators by Principal Component Analysis (PCA). The validity of the PCA model is examined by numerical taxonomy and non-parametric Spearman and Kendall-Tau correlation techniques. The economic indicators are identified by an extensive international review. This study considers auto industries of various developed and developing countries with respect to the selected indicators. To have an accurate assessment of the automotive industries and also to minimise the bias, a five-year period (1996-2000) is considered. The results of the modelling approach would help policymakers and top managers to have better understand and improve existing systems with respect to the integrated performance of auto industries.

Byline: J. Razmi, S.F. Ghaderi, P.K. Ahmed This paper illustrates the challenges and problems facing organisations in identifying a partner company to benchmark against. The paper highlights the benchmarking process and the critical role of selecting an appropriate partner(s) for benchmarking, and then proceeds to illuminate a number of conventional techniques that can be used in this process by highlighting their advantages and disadvantages. The paper then elaborates the Analytic Hierarchy Process (AHP) as a highly versatile yet simple to use method in benchmarking partner selection. The paper concludes by illustrating the use of AHP as a case example.