A soft computing approach based on critical chain for project planning and control in real-world applications with interval data
Data
2021Autorius
Aramesh, S.
Mousavi, S. M.
Mohagheghi, V.
Zavadskas, Edmundas Kazimieras
Antuchevičienė, Jurgita
Metaduomenys
Rodyti detalų aprašąSantrauka
Resource-constrained project scheduling problem (RCPSP) has been one of the most important topics in project scheduling in recent decades. RCPSP, due to the strategic importance of the projects and internal and external pressures for timely completion, is a very challenging task. When executing a project, controlling and monitoring it also becomes vital. This paper aims to present a new soft computing framework that incorporates decision making about RCPSP parameters, RCPSP modeling, adding project and activities buffer, and monitoring the project. In the decision-making procedure, the activities durations are interval, but resource requirements are real numbers. So, the decision-making problem needs a hybrid procedure. To overcome this matter, the hybrid projection measure is extended to obtain the experts weights and build the aggregated decision matrix. In the RCPSP section, the activities durations are not determined and vary between certain ranges. The resource requirements and range of activities durations are obtained from group decision-making method. In addition, this model is solved with simulated annealing (SA) algorithm. In the third step, buffers are considered in a way that allocating project buffer to activities’ buffers becomes based on a new normalized important factor. The normalized important factor is introduced by considering activity duration and resource requirements. Finally, a novel controlling procedure is extended by activity buffer monitoring. Two buffer threshold sets and violations are applied, and each one of them sends a particular alarm to the project manager. Project manager's decisions in optimistic and pessimistic situations are discussed. Ultimately, the method is solved in a real case study, and the results are discussed. The application shows that the presented method is flexible in many situations. It also increases the probability of timely completion of the project in addition to tracking the deviations from the plan. The proposed method introduces a comprehensive framework, so it gives project managers a better vision. It can also act as an ideal monitoring tool to control schedule deviations and to help project manager for proper actions during the project execution.