Journal of Industrial and Systems Engineering
Volume:5 Issue: 4, Winter 2011

Our primary aim, in this paper, is to propose and investigate, for the first time, the application of Data Envelopment Analysis (DEA) technique in assessing Iranian public universities. We provide an analysis on the importance of the stakeholder’s perspective on the structure of DEA and the variations of efficiency results. For illustrations, we perform efficiency analysis on a sample of public universities in Iran from three different perspectives of importance, i.e., teaching quality, research productivity, and cost efficiency by using available data.

In this paper, the single machine replacement problem is being modeled into the frameworks of stochastic dynamic programming and control threshold policy, where some properties of the optimal values of the control thresholds are derived. Using these properties and by minimizing a cost function, the optimal values of two control thresholds for the time between productions of two successive nonconforming products is determined. If this time exceeds the first threshold, the production continues. If it is less than the second one, inspection, repair, or replacement occur. However, if it falls within the control thresholds, then the process of sampling continues. At the end, the application of the proposed methodology is demonstrated using a numerical illustration.

The capacitated arc routing problem (CARP) is one of the most important routing problems with many applications in real world situations. In some real applications such as urban waste collection and etc., decision makers have to consider more than one objective and investigate the problem under uncertain situations where required edges have demand for more than one type of commodity. So, in this research, a new fuzzy chance constrained programming model based on credibility measure for CARP with two minimizing the number of vehicle and minimizing the total travel cost is formulated. In this model each required edge has demand for more than one type of commodity and also all demands for each commodity are supposed to be triangular fuzzy numbers. Then we develop a multi-objective genetic algorithm using the Pareto ranking technique and hybrid it with stochastic simulation to design an intelligent algorithm to solve the fuzzy chance constrained model. In order to improve the quality of final solutions, we also propose a new heuristic method to generate a good initial solution in initial population of genetic algorithm. Some data sets with fuzzy demand generated randomly are used to evaluate and investigate key characteristics of the new proposed model and solution approach.

In this paper we consider a system consisting of a supplier with a single processing unit, a repair center, and a retailer with Poisson demand. We assume that the retailer applies one-for-one ordering policy with backorders for his inventory control. The retailer’s orders form a queue in the supplier processing unit. We also assume that a certain fraction of the products produced by the supplier are defective and they must be repaired in the repair center before going to the retailer. Further, we assume that the processing time of each unit at the supplier and the service time of each defective item in the repair center are exponentially distributed random variables with known means. The purpose of this paper is to obtain the optimal value of the inventory position of the retailer which minimizes the total cost of the system. To achieve this purpose we consider two cases, Case (1) the ratio of the arrival rate to service rate, at the supplier and at the repair center are not equal and Case (2) these ratios are equal. For both cases, we first derive the long run probability distribution of the number of outstanding orders of the retailer. Then we obtain the average on hand inventory and backorders of the retailer, and derive the long run unit total cost of the system. We also investigate the convexity of this total system cost function and obtain the optimal value of the inventory position of the retailer and present a numerical example.

The following is a discussion on the different aspects of the term capacity as well as a brief look at the commonly used capacity definitions in industrial and operations engineering in general and in Civil Aviation in particular. We maintain that quality factors (including more specifically here, safety) must be explicitly considered in runway capacity definition, and accordingly, we provide a revision on previous perspectives.