Almost all time-cost trade-off models are wrongly assumed to be linear or discrete. • Two new non-linear theoretical models are proposed for construction projects. • They allow discrete/continuous, and deterministic/stochastic configurations. • Comparison of crashing and fast-tracking is mathematically analysed.
A significant proportion of projects across the construction industry fail to meet their planned completion dates, being this a recurrent topic in the project management literature. Multiples causes of project delays have been proposed, however, hardly any attention has been paid to the fact that the most celebrated project monitoring and control technique – the Earned Value Management (EVM) – may not be as fit for purpose as it seems. It is proposed that because EVM ignores activity duration variability it always results in optimistic completion dates which may be very difficult to meet in the real projects. This research offers a fresh and long overdue critique of EVM in its most common implementation (assuming deterministic activity durations and costs), while highlighting its shortcomings. Particularly, Monte Carlo simulations are implemented to exemplify how the merge event bias phenomenon is inadvertently impacting the schedule in both time and cost dimensions. A fictitious case study is used to demonstrate the connection between these shortcomings and what is then conceived as a delay in project completion.
Accelerating construction projects is a commonly used method for meeting the project deadlines and/or compensating for current delays. There are several approaches to speed-up a project, such as activity crashing and overlapping. Activity crashing means reducing activity durations through adding more resources. Activity overlapping means executing certain activities in parallel when they were supposed to be sequential in the original plan. Construction management literature is mostly focused on studying each acceleration mode separately, while the focal point of this paper is to develop a joint model and a first algorithmic implementation that involves both acceleration methods. Particularly, on reviewing the project management and scheduling literature, a mathematical model combining activity crashing and overlapping is reformulated. Also, a Genetic Algorithm is implemented on a fictitious case study. Preliminary findings of the model and algorithmic implementations identify that activity crashing alone and a mixed approach are preferred when significant compression is required, whereas activity overlapping is recommended for minimizing compression costs when only a small compression is required.
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