International Journal of Industrial Engineering & Production Research

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The dynamic nature of projects and the fact that they are carried out in changing environments, justify the need for their periodic monitoring and control. Collection of information about the performance of projects at control points costs money. The corrective actions that may need to be taken to bring the project in line with the plan also costs money. On the other hand, penalties are usually imposed when due to “no monitoring” policies projects are delivered later than expected. Thence, this paper addresses two fundamental questions in this regard. First question concerns the optimal frequency of control during the life cycle of a project. The second question concerns the optimal timing of control points. Our solution methodology consists of a simulation-optimization model that optimizes the timing of control points using the attraction-repulsion mechanisms borrowed from the electromagnetism theory. A mathematical model is also used to optimally expedite the remaining part of the project when possible delays are to be compensated.

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This paper aims at emphasizing the importance of establishing a Project Management (PM) system in Technology Transfer (TT) processes and developing a conceptual framework for it. TT is an important process in Technology Management affairs for all enterprises.  Most of the time, lack of a particular concentration on technical, commercial and legal aspects of TT process, leads to mismanagement of other aspects of transferring project, like Time and Project Integration. This situation may lead to failure and loss of many opportunities in transfer process. To overcome this problem, inputs, outputs and activities of a typical TT processes are identified and based on these components, a conceptual framework for managing this project & prevent the loss is developed using Project Management models and methodologies.

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In this paper, we consider a stochastic Time-Cost Tradeoff Problem (TCTP) in PERT networks for project management, in which all activities are subjected to a linear cost function and assumed to be exponentially distributed. The aim of this problem is to maximize the project completion probability with a pre-known deadline to a predefined probability such that the required additional cost is minimized. A single path TCTP is constructed as an optimization problem with decision variables of activity mean durations. We then reformulate the single path TCTP as a cone quadratic program in order to apply polynomial time interior point methods to solve the reformulation. Finally, we develop an iterative algorithm based on Monte Carlo simulation technique and conic optimization to solve general TCTP. The proposed approach has been tested on some randomly generated test problems. The results illustrate the good performance of our new approach.

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Abstract Project management in construction industry, in many cases, is imperfect with respect to the integration of Occupational Health and Safety (OHS) risks. This imperfection exhibits itself as complications affecting the riskiness of industrial procedures and is illustrated usually by poor awareness of OHS within project teams. Difficulties on OHS regularly came about in the construction industry. The integration of OHS risk is not systematic in construction areas in spite of progressing laws and management systems. As project safety and risk evaluation in construction industry is an important issue, thus, the way on doing evaluation and liability of estimation is necessary. In this paper, we propose a new systematic approach based on Latin Hypercube Sampling (LHS) for integrating occupational health and safety into project risk evaluation. This approach tries to identify and evaluate reinforcement effects in a systematic approach for integrating OHS risks into project risk assessment. Furthermore, the proposed method allows evaluating and comparing OHS risks before and after the mitigation plan. A case study is used to prove the workability, credibility of the risk evaluation approach and uncomplicated integration of OHS risks at a construction project. This approach enables continual revaluation of criteria over the direction of the project or when new information is obtained. This model enables the decision makers such as project managers to integrate OHS risks toward schedule plan and compare them before and after the mitigation plan. The mentioned model is found to be useful for predicting OHS risks in construction industries and thus avoiding accidents over the path of the project.

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The aim of this study is to present a new method to predict project time and cost under uncertainty. Assuming that what happens in projects implementation which is expressed in the form of Earned Value Management (EVM) indicators is primarily related to the nature of randomness or unreliability, in this study, by using Monte Carlo simulation, and assuming a specific distribution for the time and cost of project activities, a significant number of predicting scenarios will be simulated. According to the data, an artificial neural network is used as efficient data mining methods to estimate the project time and cost at completion.

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The Project Management Body of Knowledge (PMBOK) is a widely used model of project management based on prior experience. This standard does not distinguish between small and large projects, but small projects, with their limited schedules and budgets, face challenges using the extensive structure proposed by this standard. It has been suggested that the standard can be adapted to each project within its specifications; however, the tailoring procedures are complex, time-consuming, and at times impossible to apply to small projects. The present study examined whether or not the PMBOK is an appropriate model for small projects. To address this issue, a questionnaire was prepared and sent to 134 professional project managers. Analysis of the data confirmed that the assumption that PMBOK is a challenge to small projects was not contradicted. Most participants agreed that the procedure should be tailored to prioritize the standard tools and guiding techniques, in addition to the knowledge areas, for small projects.