Trade-off between time and cost in project planning: a simulation-based optimization approach

Abstract

Mine development or construction projects should be carefully scheduled to meet the project objectives in terms of duration, budget, and scope since they include many highly time- and cost-sensitive activities. The inherent complexity in mining operations, coupled with material, equipment, and resource availabilities, commodity price cyclicality, and market trend uncertainties, can lead to a high risk to the project, resulting in schedule and cost overruns. Therefore, these projects must be planned and controlled efficiently to ensure that the required capital investment does not exceed the project budget and the project deadline is met. This paper proposes a simulation-based model to optimize the trade-off between time and cost of project planning problems under uncertainty. In doing so, equally probable realizations are generated considering different project duration crashing scenarios to quantify the impact of uncertainty on the total project cost and project completion time, and risks are assessed. A numerical example is provided to show the performance of the proposed approach through an underground mine development project. Statistical analysis of the results obtained from the developed simulation model identifies the risk of project completion time, the criticality of activities, and bottleneck activities of the project. In addition, the time–cost trade-off is achieved under the project deadline and budget constraints by implementing 20,736 different crashing scenarios. Finally, the results obtained from the developed formulation are compared with those obtained from the linear programming solution. The proposed approach has a strong potential to add value to project management of mining projects.

Framework for metamodel-based design optimization considering product performance and assembly process complexity

“…One of the most popular process-oriented approaches is discrete event simulation (DES), which focuses on complex processes or systems at a high level of abstraction, typically without consideration of the specific physical properties, such as geometry, inherent to the product design. For instance, in the domain of construction projects, 24 DES is employed for optimizing project time, cost, and risk management. In manufacturing, specific process can be analyzed to assess the effects of implementing Lean Manufacturing tools 25 or to study the impact of changes in process architecture and coupling between subsystems on overall process performance.…”