International Journal of Industrial Engineering and Productional Research
Volume:23 Issue: 1, Mar 2012

Evaluative and comparative analysis among educational projects remains an issue for administration, program directors, instructors, and educational institutes. This study reports a fuzzy complexity model for educational projects, which has two primary aspects (technical aspects and transparency aspects). These aspects may not be measured precisely due to uncertain situations. Therefore, a fuzzy graph-based model to measure the relative complexity of educational projects is presented that uses an aggregation operator to resolve conflict among experts with respect to a complexity relation. The model maps the fuzzy graph into a scaled Cartesian diagram that depicts the relative degree of complexity among projects. An illustrative example for several educational projects is demonstrated to present the application of the model.

New home buyers in United States are becoming more discriminating in their home buying decision. They are demanding quality construction at reasonable prices. The current state of construction market also gives construction buyers more ammunition to be more discriminate when they choose to purchase homes. To be competitive and remain in business, housing contractors and developers must meet the growing quality demands of the customers. Thus, the competition to meet the buyers’ quality demand has forced many of them to rethink the ways they build their homes. The improved designs, and construction methods and practices have resulted into award-winning quality-built homes for many of these contractors. This study was conducted to examine the quality improvement characteristics of selected award-winning residential builders and housing developers in selected counties in North Carolina, U.S.A. Through a structured questionnaire, the researchers collected information relative to their common quality characteristics, organizational culture and overall business practices. Data analysis was performed using basic descriptive statistics. The results show that regular inspection of work in progress, feedback from customers, and immediate attention to punch list items, were highly ranked among the quality characteristics evaluated.

As functional integration has increased in hand-held consumer devices features such as Global Positioning System (GPS) receivers have been embedded in increasingly more devices in recent years. For example, the train positioning system based on GPS provides an integrated positioning solution which can be used in many rail applications without a cost intensive infrastructure. The network built in the GPS receiver has the advantage of determining the exact location and time of the train. The objective of this research was to develop a system which accepts the location from the GPS receiver mounted on the train and extracts its local time. This is implemented using Altera SOPC builder in the NIOS – II environment. Nios II is a 32 bit soft-core embedded-processor architecture designed specifically for the Altera family of FPGAs. The signal received using the GPS receiver is given to the DE2 board through the UART port and converted it in to local time and displayed on the NIOS II console. A working system was developed, which accepts the location from the GPS receiver and extracted its local time.

An interactive heuristic approach can offer a practical solution to the problem of linear integer programming (LIP) by combining an optimization technique with the Decision Maker’s (DM) judgment and technical supervision. This is made possible using the concept of bicriterion linear programming (BLP) problem in an integer environment. This model proposes two bicriterion linear programs for identifying a feasible solution point when an initial infeasible solution point is provided by the decision maker or when the searching process leaves the region of feasibility seeking for a better pattern to improve the objective function. Instructions regarding the structure of such BLP problems are broadly discussed. This added property offers a great degree of flexibility to the decision making problem solving process.The heuristic engine is comprised of four algorithms: Improve, Feasible, Leave, and Backtrack. In each iteration, when a selected algorithm has been terminated, the DM is presented with the results and asked to reevaluate the solution process by choosing an appropriate algorithm to follow. It is shown that the method converges to the optimal solution for most of the time. A solution technique for solving such a problem is introduced with sufficient details.

One of the main principles of the passive defense is the principle of site selection. In this paper, we propose a multiple objective nonlinear programming model that considers the principle of the site selection in terms of two qualitative and quantitative aspects. The purpose of the proposed model is selection of the place of key production facilities of a system in which not only it observes the dispersion principle but also reduces the system transportation costs. Moreover, the proposed model tries to select the sites that can fulfill other elements of site selection as well as dispersion in a way that it increases the trustworthiness of the selected network. For solving the proposed model we used the Genetic Algorithm integrated with TOPSIS method.

Until now single values of IRR are traditionally used to estimate the time value of cash flows. Since uncertainty exists in estimating cost data, the resulting decision may not be reliable. The most commonly cited drawbacks to using the internal rate of return in evaluatton of deterministic cash flow streams is the possibility of multiple conflicting internal rates of return. In this paper we present a fuzzy methodology for solving problems of multiple IRR in any type of streams. Utilization of fuzzy cash flow allows modeling of uncertainty in estimating cost data. The approach of -cut is to decrease the range of the final fuzzy set by increasing the degree of membership. For each fuzzy IRR in an optimum -cut, and an obtained present value of each stream, it is possible to decide on acceptance or rejection of a project according to the type of each stream (borrowing or investing). The upper bound of -cut is the worst case for borrowing and the lower bound of -cut is the worst case for investing. It is shown that both the internal rate of return and the present value are important in decision making and by analyzing the sensitivity of these values relative to the -cut variation, one can see the behavior of the project and choose a narrower fuzzy range.

Fuzzy Logic is one of the concepts that has created different scientific attitudes by entering into various professional fields nowadays and in some cases has made remarkable effects on the results of the practical researches. However, the existence of stochastic and uncertain situations in risk and accident field, affects the possibility of the forecasting and preventing the occurrence of the accident and the undesired results of it.In this paper, fuzzy approach is used for risk evaluating and forecasting, in accidents caused by working with vehicles such as lift truck. Basically, by using fuzzy rules in forecasting various accident scenarios, considering all input variables of research problem, the uncertainty space in the research subject is reduced to the possible minimum state and a better capability of accident forecasting is created in comparison to the classic two-valued situations. This new approach helps the senior managers make decisions in risk and accident management with stronger scientific support and more reliably.

Inventory control is one of the most important issues in supply chain management. In this paper, a three-echelon production, distribution, inventory system composed of one producer, a set of wholesalers and retailers is considered. Costumer's demands can be approximated by a normal distribution and the inventory policy is a kind of continuous review (R, Q). In this paper, a model based on standard cost structure of inventory systems is developed and a heuristic algorithm is designed to optimize the developed model. The application of model is examined in a series of designed experiments that are compared with simulation results. These comparisons verify the validity of the model. Regarding to real complexities in three-echelon systems analysis, the proposed method can have a wide application in practical problems with the same considerations and assumptions. In addition, this method can be used to approximate those systems that follow a Poisson demand.