Abstract
The resource constrained project-scheduling problem (RCPSP) aims to minimize the duration of a project. RCPSP is prevalently used in programming the projects with high number of activities and resources such as construction projects. In this study, 240 projects such as residential, office, school, etc. are designed and programmed under limited resources. The resource amounts of these projects are determined using three priority rules, these are Latest Finish Time, Minimum Slack Time and Maximum Remaining Path Length which have the highest performance according to the literature, in the amounts of 2, 4, 6 and 8. The project times are estimated using artificial neural network (ANN). A correlation coefficient of 0.70 was obtained from the ANN estimation model.
Highlights
The optimum allocation of restricted resources over time is the principal concern of project scheduling, which thereby handles the task of defining the set of activities to be carried out at a particular point in time; in addition to playing a significant role in various fields of engineering (Idoro 2012)
It is quite difficult to estimate which project time and priority rule exhibits the best performance under the conditions of constrained resources
An extensive review of the similar studies in the literature reveals that the performance of priority rules depend on several factors such as project type, the scope of project, number of resources and restrictions etc
Summary
The optimum allocation of restricted resources over time is the principal concern of project scheduling, which thereby handles the task of defining the set of activities to be carried out at a particular point in time; in addition to playing a significant role in various fields of engineering (Idoro 2012). The heuristic method can be defined as a means of facilitating the process of reaching the optimal solution group through following a simple rule (Demeulemeester, Herroelen 1992). It focuses on two basic concepts; the first one is minimizing the time (Slowinski 1980; Talbot 1982; Jaśkowski, Sobotka 2004), and the second one is minimizing the project cost (Padman, Smith-Daniels 1993; Yang et al.1993). The resource amounts of these projects are determined using 3 priority rules, these are LFT, MNSLCK and MRPL which have the highest performance according to the literature The obtained data will be entered into the artificial neural network (ANN) database to develop training and testing set of ANN models
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