Abstract
During the execution of construction projects, uncertain events, such as delays, prolongations and disruptions of project activities, have the potential to cause a significant deviation between the planned and realized state of a project. As a result, progress on important project objectives can decrease and this leads to critical delays as well as heavy profit loss. For this reason, we propose the implementation of the customized evolutionary algorithm to generate resilient baseline schedules which include a sufficient number of time floats to absorb the negative impact of uncertainty. This way, the baseline solution is searched as a trade-off between project duration, its final profit and the overall baseline stability. The proposed algorithm is applied to real construction project data and the results of the analysis suggest improved stability for resilient baseline schedules. Application of the genetic algorithm to solve the existing multi-objective problem enables practical implementation of new technologies and methods in construction management. Resilient baseline schedules can be used in an uncertain environment to achieve more accurate predictions and support decision making in the areas of construction scheduling and costing.
Highlights
Construction projects are performed in complex dynamic surroundings where uncertainty and risk can negatively affect the achievement of time, budget, and quality goals [1]
A realization of forecasted project goals depends on calculating reliable baseline schedules, where the goal is to minimize project duration or maximize final profit and to minimize the deviation between the planned and realized state
Research in resilient project scheduling has relied more on the second interpretation of resilience, investigating the proactive methods for building reliable baseline schedules with the increased ability to absorb the negative impact of uncertainty throughout the execution state
Summary
Construction projects are performed in complex dynamic surroundings where uncertainty and risk can negatively affect the achievement of time, budget, and quality goals [1]. In the construction industry, it is extremely important to effectively manage project objectives such as duration, cost and quality, as well as the associated uncertainty [2]. For this reason, a realization of forecasted project goals depends on calculating reliable baseline schedules, where the goal is to minimize project duration or maximize final profit and to minimize the deviation between the planned and realized state. Research in resilient project scheduling has relied more on the second interpretation of resilience, investigating the proactive methods for building reliable baseline schedules with the increased ability to absorb the negative impact of uncertainty throughout the execution state
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