INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING AND PRODUCTION MANAGEMENT (IJIE) (INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE) (PERSIAN)
Year:2009 | Volume:19 | Issue:4|Papers Count:12

Because of Emergence of new technology area, knowledge economy and globalization challenges, Science & technology policy making is not an easy process like prioritizing some technology. Nowadays Science & technology policy making is complex systematic processes that consist all aspect of the society. This paper tries to analyze oncoming science and technology policy-making challenges and scenarios in I.R. Iran. For this propose paper, first attend to study and combine economic, management, scientific, technological, sociological and global paradigm changes and it’s affects on organization, firms and societies, for gaining true consideration from difficulties and complexities oncoming in science and technology policy-making; Second initiate domestic Iranian perspective and challenges; in third step review different appropriate policy formulation model, methods and instruments and finally discuss some Vis A Vis scenarios.

Analyzing different issues of most systems, particularly their design, implementation, and development, requires some sort of techniques which are capable of studying their special conditions in stochastic states. Simulation is regarded as one of the most efficient methods for this purpose in the area of engineering, systems, and management. Studying and analyzing a system under special, critical, and stochastic conditions is one of the capabilities and advantages of simulation. This unique feature of simulation strongly depends on random numbers. Some of the simulation scientists believe that random numbers act as nuts and bolts of simulation. The more random numbers satisfy randomness criteria, the more effective the model and simulation results would be. In this paper, initially, different random number streams- in a more accurate term pseudo random number streams- will be studied. Then, some of the common and simple methods of random number generation will be elaborated. Obviously, the results show that random numbers which are generated by these simple methods suffer from dispersion. Ultimately we attempt to introduce an enhanced hybrid random number generation method based on a combination of these common methods.

This paper illustrates how common platform (CP) strategy can contribute to the effectiveness of the supply chain through commonality. Through reviewing the related literature and the practical data, which are collected through observations in manufacturing, a mathematical model is set up. This model was developed for reducing cost of part commonality in SCM and solved it by simulated annealing approach. Through applying this concept, chain members can reduce manufacturing variability, i.e. the variety of parts, materials, components, etc, and thereby enable companies to increase value by producing a variety of products. One can say that the logics of applying CP and commonality in manufacturing area is, to simplify the offering and processing of products in order to reduce the parts variety. This will be accomplished through standardizing components and resource sharing strategies, and will result in the costs and time reduction, and other non value added factors. This work is one of the first to present SCM based on CP concept for supporting decision makers. The main research questions include: 1) Why CP in SCM to be applied? 2) Which combination of commonality is suitable for reduce part and component variety, 3) how much cost saving obtain, and how can we contribute to its application.

In the past few decades along with the developing industrial units, the use of multi floor factories has increased. On the other hand according to the service provided and being in city centers, office buildings, hospitals, universities, ministries etc. represent the most multi floor buildings. One of the most costly procedures which these factories and buildings (which are multi floored) face is the cost of transporting equipment among different departments. These transportations are divided into horizontal and vertical, according to being a multi floor building. For vertical transportation the machine always recommended is an elevator. Placing and elevator is a costly procedure, therefore the number of elevators needed and their locations should be decided. Since 1967 a number of algorithms have been introduced to solve multi floor buildings designing problems, using a lot of simplifying theories based on the large amount of calculations needed. Therefore they are only described theoretically and mathematically, but can't be used in a real setting. In this research we have tried to define an algorithm to solve multi floor designing problem so that it could be used in real settings. All the simplifying theories used for the previous algorithms have been eliminated. Results show that this algorithm to a large extent can be applied to real settings.

Several sampling distribution properties of the estimator for Cpk are presented under the assumption that the data are normal, independent and identically distributed. In this paper using these assumptions, the expectation, variance and skewness are calculated by statistical methods, since the sampling distribution is weakly skewed, it is concluded that a symmetric interval estimator for Cpk might be reasonable. Also a symmetric interval estimator has been developed.

In this paper, after applying Response Surface Methodology (RSM) for Robust Parameter Design, we take into account two equations representing the mean and variance responses. Then, the control factors are determined such that these two objective functions are close to their ideal values. In this regard, the Lp method is used and its sensitivity analysis is accomplished through a numerical example for the larger- the better case. Moreover, in this study the impact of ignoring uncontrollable noise factors in estimation of the optimum points are investigated.

In the organizational studies, the measurement of organizational learning capabilities has become an increasingly important area. There are several models in literature that have been generated by statistical data from manufacturing firms. In this paper we have used a structural equation model for measurement of organizational learning in hospitals as services firms. In our model, there are four dimensions for organizational learning measuring: managerial commitment, systems perspective, openness and experimentation, and knowledge transfer and integration. The results imply that organizational learning is measurable by these four dimensions. The model could be use to improve learning capability by managers. However, the average of knowledge transfer and integration capability and managerial commitment capability is the highest and the lowest averages respectively. Comparison of our results with previous studies implies that being the service firm as a human-based organization lead to improvement of system perspective and knowledge transfer and integration capabilities.

This paper presents a multi-mode resource-constrained project scheduling problem (MRCPSP) with maximizing the net present value (NPV) form the project contractor’s point of view. Positive and negative cash flows are considered in this model. Furthermore, to make the model close to the real situations, four different models for positive cash flows are considered. Two meta-heuristics, called simulated annealing and genetic algorithms, are used in order to solve the proposed model of the forgoing problem. To schedule all activities, a bi-directional scheduling generation scheme (SGS) for the multi-mode version is proposed, and the activity list structure selects for presenting a permutation of activities. Finally, computational results for a set of test problems taken from the project scheduling problem library (PSPLIB) are presented and discussed.

In this paper, multi-objective set covering problems (MOSCP) as one of the location-allocation models are being considered. Here, the objective is to minimize the cost of locating facilities and at the same time to maximize demand satisfaction in a defined structure so that each customer or zone is being covered by at least one facility. Since the problem falls into NP-hard category from the complexity point of view, it cannot be solved in a reasonable computational time period by an exact algorithm. For this reason, a Simulated Annealing (SA) algorithm is proposed to solve MOSCP. The algorithm is a meta-heuristic approach coupled with a neighborhood search technique.The validity and quality of the proposed method is tested by solving benchmark problems and the results obtained were quite satisfactory.

This paper, introduces a new problem in the field of combinatorial problems as Consumers Adjacency Problem (CAP). Assume a set of resources with specific utility values. Also assume a set of consumers that are common in the resources. Each of packing of the consumers is one of the solution space points. In a given packing, if whole consumers of a given resource are continuous adjacent, the utility value of the resource adds to the objective function. It is desired to determine the suitable pack the consumers in order to have the maximum sum of utility value of resources. To the one-dimensional problem, in this paper, a formulation based on the mathematical programming is provided and a heuristic solving method is introduced. Also, as a useful application, project risk ranking by CAP is discussed.

This paper suggests a composed option pricing model based on black-scholes and binomial tree models. So at first this two models are presented and analyzed. Then we showed black-scholes model is an appropriate option pricing model for stocks with low volatility and binomial trees model is an appropriate option pricing model for stocks with high volatility. Suggested model is a composed model of black-scholes and binomial tree models and volatility is used as selecting model factor. To determine volatility limit quantity, we calculated average volatility of Iran Stock Exchange. For this calculating we selected 32 stocks in two period of time. At the end of paper, suggested model is validated by 2 methods and it’s validity is approved by both of them.