In spite of the vast amount of studies on green supplier selection and related methods and approaches, the evaluation of green supply chain performance indicators aligned with classic measures is less investigated. Therefore, this research attempted to provide an integrated step by step procedure to consider both classical and green key performance indicators within the supplier selection framework. A literature survey was conducted and measures for assessing the green suppliers were extracted. Nominal Group Technique (NGT) is deployed to extract the most critical performance measures. Ten performance measures were selected as a substitute for green supplier selection. A Fuzzy Analytical Network Process (FANP) was then deployed to weight the extracted measures and determine their importance level.

In the manufacturing industry, managers and engineers are trying to sustain their competitiveness by achieving high output and productivity. There are some common problems such as waiting times, failures, reworks in production line that impose extra cost to the companies. Therefore, companies are striving to find methods in order to determine and deal with problems using different methods such as mathematical, statistical and computer simulation. The goal of this paper is to increase the total output production and to improve productivity using computer simulation and Taguchi method. This paper introduces a color manufacturing line as a case study which is simulated using arena 13.9 software. Following that the Taguchi method is applied to assess the effect of controllable and uncontrollable factors on the total output production. According to the result of JMP 10 software to conduct Taguchi experiment, the maximum desirability of productivity will be achieved when the value of factors such service rate of delpak machine=UNIF (30, 40), number of labor=14, inspection time=120 and number of Permil=5. Taguchi Method plays an efficient and suitable role in the process improvement, proposing adjustments that will provide an improvement in the productivity.

One of the most controversial issues in construction management is performance measurement. Construction managers are always involved in evaluation of resource changes which effect process performance. Due to limitations and also cost of resources, resource allocation has become a complex task in construction projects. To evaluate the effects of different resources on total project performance, managers strive to allocate limited resources by determining resource combinations. This paper aims at conducting Taguchi method along with computer simulation to determine the optimum combination of resources for a real world case study involving a concrete pouring operation in order to reduce cycle time and process costs. The proposed simulation model was conducted under Arena 13.9. Final result shows that the optimum resource combination will be achieved when all of resources are located in the low level. This means that number of trucks, spreader crew, vibrator crew and finisher crew should be equal to 3, 1, 1, and 1 respectively to improve the total performance.

Queuing problems present a gap in the availability of knowledge at port container terminals. This study is focused on various types of services for port container terminal queuing system. The purpose of this paper is to introduce a methodology to decrease waiting time without any reduction in productivity. A new approach for servicing at the queue is proposed, and with this idea waiting time will be reduced without any change in productivity or additional cost. To execute this approach in a port container terminal, berthing areas of the port are simulated with ARENA 13.5, and this new approach is implemented in the model. The result of this change are compared with results of a port container terminal as case study. With implementing this method the waiting time is reduced dramatically and productivity increased slowly.

The present study aims to investigate the optimized profile of the body through minimizing the Drag coefficient in certain Reynolds regime. For this purpose, effective aerodynamic computations are required to find the Drag coefficient. Then, the computations should be coupled thorough an optimization process to obtain the optimized profile. The aerodynamic computations include calculating the surrounding potential flow field of an object, calculating the laminar and turbulent boundary layer close to the object, and calculating the Drag coefficient of the object’s body surface. To optimize the profile, indirect methods are used to calculate the potential flow since the object profile is initially amorphous. In addition to the indirect methods, the present study has also used axial singularity method which is more precise and efficient compared to other methods. In this method, the body profile is not optimized directly. Instead, a sink-and-source singularity distribution is used on the axis to model the body profile and calculate the relevant viscose flow field.