IRANIAN JOURNAL OF OPTIMIZATION
Year:2009 | Volume:1 | Issue:3|Papers Count:7

In models of data envelopment analysis (DEA), an optimal set of weights is generally assumed to represent the assessed decision making unit (DMU) in the best light in comparison to all the other DMU s, and so there is an optimal set of weights corresponding to each DMU. The present paper, proposes a three stage method to determine one common set of weights for decision making units. Then, we use these weights to rank efficient units. We demonstrate the approach by applying it to rank gas companies.

This paper investigates a procedure for identifying all efficient hyperplanes of production possibility set (PPS). This procedure is based on a method which recommended by Pekka J. Korhonen [8]. He offered using of lexicographic parametric programming method for recognizing all efficient units in data envelopment analysis (DEA). In this paper we can find efficient hyperplanes, via using the parameterization of the right hand side vector of the envelopment problem of each efficient unit.

There have been many productive methods developed so far for optimization of multiple response surface (MRS) problems. This paper tends to review the most seminal approaches in MRS and discuss the strength and weakness of each of the approaches through existing aspects in MRS. A numerical example is included to compare results by different methods. Finally, some of the prominent areas for future research discussed by different researchers are presented.

This paper reports a survey and case study research outcomes on the application of Data Envelopment Analysis (DEA) to the ranking method of European Foundation for Quality Management (EFQM) Business Excellence Model in Iran’s Automotive Industry and improving benchmarking process after assessment. Following the global trend, the Iranian industry leaders have introduced the EFQM practice to their supply chain in order to improve the supply base competitiveness during the last four years. A question which is raises is whether the EFQM model can be combined with a mathematical model such as DEA in order to generate a new ranking method and develop or facilitate the benchmarking process. The developed model of this paper is simple. However, it provides some new and interesting insights. The paper assesses the usefulness and capability of the DEA technique to recognize a new scoring system in order to compare the classical ranking method and the EFQM business model. We used this method to identify meaningful exemplar companies for each criterion of the EFQM model then we designed a road map based on realistic targets in the criterion which have currently been achieved by exemplar companies. The research indicates that the DEA approach is a reliable tool to analyze the latent knowledge of scores generated by conducting self assessments.The Wilcoxon Rank Sum Test is used to compare two scores and the Test of Hypothesis reveals the meaningful relation between the EFQM and DEA new ranking methods.Finally, we drew a road map based on the benchmarking concept using the research results.

Research interests have been focused on the concept of penalizing jobs both for being early and for being tardy because not only of modern competitive industrial challenges of providing a variety of products at a very low cost by smoothing productions but also of its increasing and exciting computer applications. Here, sequencing approaches of the mixedmodel just-in-time production systems is reviewed. In this note, realizing a need of critical review, a survey on the elegant mathematical models, methods and complexity of the mixedmodel just-in-time sequencing problem with an insight into the existing analytical literature is given. The established research results together with open problems and possible extensions are presented.

In this paper, Chebyshev acceleration technique is used to solve the fuzzy linear system (FLS). This method is discussed in details and followed by summary of some other acceleration techniques. Moreover, we show that in some situations that the methods such as Jacobi, Gauss-Sidel, SOR and conjugate gradient is divergent, our proposed method is applicable and the acquired results are illustrated by some numerical examples.

In this paper the substantiation of the method of full averaging for fuzzy differential inclusions is considered. These results generalize the results of [17, 20] for differential inclusions with Hukuhara derivative and of [18] for fuzzy differential equations.