Resource-constrained scheduling of construction projects and simulation of the entropy impact on a project’s duration and cost
Ημερομηνία
2017Source
International Journal of Project Organisation and ManagementVolume
4Issue
4Pages
322-338Google Scholar check
Metadata
Εμφάνιση πλήρους εγγραφήςΕπιτομή
The paper reports on research work about the relationship between project resources and the entropy generated during construction, as well as on the development of a related mathematical model that utilises entropy for resource-constrained scheduling. The aim is to optimise the allocation of resources by use of an entropy metric, to study the delays which occur during a project and to relate them with the resources and the project?s entropy. Entropy is taken as the disorder brought about by the fluctuation of resources and a higher entropy value relates to a higher risk in terms of schedule completion. The reported case study shows that a significant reduction in time (up to 25.7%) can be achieved by utilising the entropy method. Furthermore, should a resource constraint be imposed then the entropy approach results in a schedule that shows a 6.25% improvement in duration (and 8% in profit) over classical scheduling methods. The paper reports on research work about the relationship between project resources and the entropy generated during construction, as well as on the development of a related mathematical model that utilises entropy for resource-constrained scheduling. The aim is to optimise the allocation of resources by use of an entropy metric, to study the delays which occur during a project and to relate them with the resources and the project?s entropy. Entropy is taken as the disorder brought about by the fluctuation of resources and a higher entropy value relates to a higher risk in terms of schedule completion. The reported case study shows that a significant reduction in time (up to 25.7%) can be achieved by utilising the entropy method. Furthermore, should a resource constraint be imposed then the entropy approach results in a schedule that shows a 6.25% improvement in duration (and 8% in profit) over classical scheduling methods.