Resilient Project Scheduling Using Artificial Intelligence: A Conceptual Framework

Dahmani, Sarra; Ben-Ammar, Oussama; Jebali, Aïda

doi:10.1007/978-3-030-85874-2_33

Cited by 5 publications

(1 citation statement)

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“…Smjernice za implementaciju koncepta rezistencije po upravljačkim razinama s primjenom na vremensko planiranje projekata, prilagođeno prema Geambasu [24] Slika 2.2. Proaktivno vremensko planiranje, prilagođeno prema [28] Slika 2.3. Projektna mreža za ilustraciju problema rezistentnog vremenskog planiranja…”

Section: Algoritam Za Proračun Resursno-tehnološke Vremenske Rezerveunclassified

Multi-objective Optimisation Model for Resilient Construction Scheduling under Uncertain Conditions

Milat¹

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Construction projects are complex undertakings that involve a large number of participants, while their realization is limited by available resources. Moreover, competitive market conditions impose short deadlines and high performance standards, that negatively impact uncertain conditions of project execution. In order to enhance the reliability in the planning process of construction projects, this doctoral research applies optimization methods for creating resilient baseline schedules. In the context of project scheduling, resilience is described as a proactive approach that minimizes the deviations between planned and realized states. This is achieved through suitable allocation of time floats, so the ability of the baseline plan to absorb uncertain impacts is improved. Hence, reliability is improved in the domain of construction management under uncertainty. This doctoral dissertation describes the novel multi-objective optimization model which can be used to enable the creation of a reliable baseline plan for a construction project. The result of the optimization process is depicted as the set of alternative baseline proposals. Further simulation and taxonomic analysis illustrate the impact of uncertainty on the project objectives. Therefore, an analytical assessment of resilience considering the potential baseline solutions facilitates decision making in construction management. Results of this research have shown that the application of the proposed methodology for proactive resilient scheduling reduces the negative impact of uncertainty. Moreover, by use of the customized metaheuristic algorithm, it is shown that the proposed resilient scheduling approach leads to more accurate forecasting and the planning calculations for a complex construction project can be accepted with increased confidence levels.

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Section: Algoritam Za Proračun Resursno-tehnološke Vremenske Rezerveunclassified