scholarly journals An Overview of Recent Research Results and Future Research Avenues Using Simulation Studies in Project Management

2013 ◽  
Vol 2013 ◽  
pp. 1-19 ◽  
Author(s):  
Mario Vanhoucke

This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented.

2021 ◽  
Vol 11 (2) ◽  
pp. 650
Author(s):  
Muritala Adebayo Isah ◽  
Byung-Soo Kim

Construction projects are planned in a complex and dynamic environment characterized by high risks and uncertainties amidst resource constraints. Assessing construction schedule risk facilitates informed decision-making, especially in a resource-constrained situation, and allows proactive actions to be taken so that project objectives are not jeopardized. This study presents a stochastic multiskilled resource scheduling (SMSRS) model for resource-constrained project scheduling problems (RCSPSP) considering the impact of risk and uncertainty on activity durations. The SMSRS model was developed by integrating a schedule risk analysis (SRA) model (developed in MS Excel) with an existing multiskilled resource scheduling (MSRS) algorithm for the development of a feasible and realistic schedule. The computational experiment carried out on three case projects using the proposed SMSRS model revealed an average percentage deviation of 10.50%, indicating the inherent risk and uncertainty in activity durations of the project schedule. The core contribution of the proposed SMSRS model is that it: (1) presents project practitioners with a simple tool for assessing the risks and uncertainty associated with resource-constrained project schedules so that necessary response actions can be taken to ensure project success; (2) provides the small-scale construction businesses with an affordable tool for evaluating schedule risk and developing a feasible and realistic project schedule.


Author(s):  
Colin H. Cropley

Time and cost outcomes of large and complex projects are forecast poorly across all sectors. Over recent years, Monte Carlo (MC) simulation has increasingly been adopted to forecast project time and cost outcomes more realistically. It is recognised that the simultaneous analysis of time and cost impacts makes sense as a modelling objective, due to the well-known relationship of time and money in projects. But most MC practitioners advocate the use of Schedule Risk Analysis (SRA) feeding into Cost Risk Analysis (CRA) because they believe it is too hard to perform Integrated Cost & Schedule Risk Analysis (IRA) realistically. This chapter elaborates an IRA methodology that produces realistic forecasts without relying on questionable assumptions and enables identification and ranking of all sources of cost uncertainty for risk optimisation as part of the process. It also describes an extension of IRA methodology to include assessment of the assets produced by the project as well as the project itself, thus enabling the analysis of business risks as well as project risks.


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