Journal of Operational Research in its Applications
Year:2015 | Volume:12 | Issue:2 (45)|Papers Count:8

Although different super-efficiency methods have been presented in the classical data envelopment analysis, classical super-efficiency methods have not, so far, received due attention in the ordinal data envelopment analysis, as a kind of imprecise data. In the present paper a classical super-efficiency model in the imprecise data envelopment analysis (IDEA) has been studied. In fact, with the assumption that the input and output data are imprecise, the relevant imprecise model (AP) has been defined. In order to solve the resulting model, we obtained its deterministic equivalent. For simplicity, using the procedure of making ordinal exact data (the converting of ordinal data into exact data), we converted the model deterministic equivalent, which is nonlinear, into an interval model. Then, based on an adaptation of Despotis and Smirlise method, we converted the resulting model into a linear programming, and having solved it under the best and the worst conditions; we obtained an interval optimal solution, the obtained optimal value being in the interval.

One of the most important functions of manufacturers and producers related to supply chain management issues and decisions is supply chain order management. But in this way, there are several problems like (a) selection best order portfolio between received orders and (b) detailed and accurate calculation of order fulfilling costs. According to these matters, In order to increase model confidence in the research, we use both robust optimization and system dynamic to manage one of the Automakers Company supply chain orders. In this supply chain, we study process of order management that include two product. In phase 1, we use robust optimization approach to determine optimum order portfolio received supply chain. In phase 2, using phase 1 output and system dynamic approach, determine costs of order fulfillment. In other word, in this phase, using system dynamic approach, we modify each order cost. Furthermore, In order to better determine cost of orders, we use activity-based costing technique to calculate cost parameter and objects. Ultimately we use simulation to validating the model. Result show, system dynamic can be a complement technique to determine more accurate cost of order fulfillment.

The present paper considers geometric shape optimization of structures that are modelled by PDEs with random data. Random data appears in inputs and parameters of the PDE. Theoretical bases are presented, and the perturbation of the identity method is applied for transforming the shape optimization problem into a fixed domain and then formulated as a stochastic optimal control problem. Random data is taken as random fields that are approximated by Karhunen-Loeve expansion. Uncertainty quantification is performed by applying non-intrusive techniques e.g., stochastic collocation method. Gradient method is applied for optimization. Numerical result is represented in order to illustrate the applicability of the proposed method.

This study attempts to presents a coherent and reliable framework to collect and rank criteria and sub criteria for selecting the most appropriate logistics service provider (3pl) for the studied company. This approach, combining quality function deployment (QFD), analytical hierarchy process (AHP) and fuzzy set theory, to evaluate and select the optimal criteria and sub criteria. In the first step the management team (stakeholders) ranked the organizational departments. Since these comments are qualitative and uncertain, the fuzzy set theory is therefore incorporated into the traditional AHP to enable company stakeholders to express their linguistic preferences, and to transform those preferences into the quantitative form for comparison. In the approach, criteria and sub criteria affecting this process are derived from the literature with respect to the academic and industrial experts’ opinions. To enable the ‘‘voice’’ of company stakeholders, HOQ, a technique of QFD, is responsible for translating the requirements of company stakeholders into evaluating criteria.It should be noted that in this study, in general, there are seven main criteria and eighteen sub-criteria which were investigated.

In this paper a new method of estimation, named Adjusted Probability Weighted Moment (APWM), is introduced which is an extension of the Probability Weighted Moment (PWM). Based on APWM, a statistical inference is carried out on the parameter of Uniform distribution on (0, q). The results are compared with the ones of the other methods like the Maximum Likelihood (ML) and PWM. The APWM outperforms the PWM and gives the results at least similar to ML.

Today, evaluation of the performance and the measurement of efficiency are as one of the effective factors in the success of Banks. The results of efficiency computation enable organizations to find better recognition of the performance of self-units. DEA is suitable method for efficiency computation of maker-decision units but one of defects of classic DEA models is to change weight each input and output for ever time of implementation of model. Also in classic methods, primary inputs and final outputs of units under control consider only and internal activities and organizational interaction ignore. In this research, we attain efficiency computation through problem solving methods with multi-goals and its solving with helping common weights for maker-decision units. Also organizational interaction evaluates in the evaluation of the branch of Bank with usage of network DEA. Statistical population is thirty seven branches in Tehran for this study that consider in the form of two phases. First phase (productive phase) includes of two inputs and five outputs and second phase or source devotion (profiting) includes five inputs (outputs of first phase) and four outputs that we compute with the use of suggested method and GAMS software of efficiency of phases and general efficiency of branches with two procedures of different weights (optimistic state) and common weight (pessimistic state) and then we analyze the findings.

Data Envelopment Analysis (DEA) is one of the successful evaluation methods for measuring the relative efficiency of Decision Making Units (DMUs) that utilizes techniques of mathematical programming. In DEA models, for measuring the relative efficiency of DMUs, for a large dataset with many inputs/outputs would need to have a long time with a huge computer. This paper developed the Genetic Algorithm (GA) for DEA. GA requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large datasets. Since the operators have important roles on the fitness of the algorithms, all the operators and parameters are calibrated by means of the Taguchi experimental design in order to improve their performances.

In today's world, the role and importance of financial system and in a relation of it, financial institutes, especially Banks, is quite conspicuous in economic development of our country. The Sustainable economic development is not possible without financial development. Banks as a responsible for finical segment of country economy and because of the rate of politics influence of this segment in whole society have a significant role in creation and reservation of sustainable economic growth. Nowadays, in consideration of sufficient number of Banks and financial institutes in country, and also according to the process of privatization of public banks, the evaluation of performance finds the particular significance. Therefore, country Banks which have abundant branches and are active in verity contexts needs to survey the evaluation of performance of units and manpower for survival and contest in this dynamics environment. If good methods and index will be introduced, superior managers can guide their employees better towards the strategic goals of their organization. In addition, they can determine the simulative methods based on appropriate motive to abet their employees and also punish them in time of needs. In this study, we investigate the effective elements on the function of human resource and branches of Saderat bank of Guilan. Then, we present a proper method in the base of Data Envelopment Analysis method (DEA) and evaluate the performance of managers of this bank branches based on their individual and functional parameters. At the end, we will propose a solution by identity of strengths and weaknesses in order to increase the efficiency.