Journal of Industrial Engineering and Management Studies

Abstract During the past decades, various models were presented to estimate project duration but, we usually face with this problem that why the estimated values for finish time of the activities and the project don’t match with the actual values and there is always a huge gap between the estimated finish time of the project and the actual finish time of the project. The oldest method that has been widely used in the past decades is the Earned Value Management (EVM) methodology, which estimates the completion time of the project based on cost indicators. During the past years, researchers have developed new models such as Earned Duration Management (EDM), Earned Schedule Management (ESM) that each of them has tried to reduce the prediction error by focusing on the indicators presented in their proposed models. In this research, the Earned Resource Management (ERM) model has been developed, which present indicators for measuring the performance of activities based on the resources provided for the implementation of project activities, as well as the progress of project activities using these resources. It is a more suitable basis for evaluating how activities are implemented and also estimating their finish time. The proposed model is implemented on a construction project and the results show that the Mean absolute percentage error (MAPE) is about 3.12%, at the end of the project which is lower than other presented methods.

Abstract The design of control chart has economic consequences that pure statistical viewpoint does not consider them. The economic-statistical design of control chart, attends not only statistical properties such as average time to signal (ATS) but also economic consequences like hourly expected total cost. The x-bar control chart dominates others if the quality is measured by continuous scale. This paper has considered the economic-statistical design of variable sample size and sampling interval (VSSI) x-bar control chart with multiple assignable causes. Using three sample sizes and three sampling intervals to construct the VSSI x-bar control chart and considering possible combination of design parameters as a decision-making unit, are part of novelty of this research. The problem is formulated as multiple objective decision making (MODM). Also, one capable hybrid meta-heuristic based on genetic algorithm is developed in this research and it was compared with some approaches extracted from the literature and it is found that it can be competitive based on economic and statistics factors.