A New Decision Support System for Optimal Integrated Project Scheduling and Resource Planning

Background And Literature Review

The mathematical framework introduced in this study is relatively generic and modifiable for solving various Resource Constrained Project Scheduling Problems (RCPSP). In this paper, the model has been utilized to solve the specific problem of optimal integration of project activity scheduling and construction equipment planning. Because of this and due to the specific structure of each optimization problem, authors have focused the literature review on studies which specifically target the relevant RCPSPs.

Among conventional optimization approaches, Integer Programming (IP) has been commonly used to model the resource loaded scheduling problem. Lee and Gatton (1994) presented a complete IP formulation that combined construction activity scheduling with the resource utilization plan. However, because of the application of prioritization rules in the resource allocation process, their proposed solution was suboptimal. Younis and Saad (1996) proposed a model for optimal resource allocation and leveling in multi-resource type projects. In their study, a solution algorithm was proposed based on principles of explicit enumeration. The model performs Critical Path Method (CPM) calculations, finds all feasible matches between activity schedules and given resource availability plan by enumeration, and finally finds the cost optimal solution by comparing costs of all feasible solutions. Since the model is based on explicit enumeration, its efficiency drops significantly as the size of the problems grows. In the same line of research, branch and bound solution approaches by Herroelen and De Reyck (1998) and Dorndorf and Pesch (2000) are major developments.

In the heuristic line of research, Hegazy (1999) developed a Genethic Algorithm (GA) metaheuristic for finding a solution for resource allocation and leveling problems. Also, Lu and Li (2003) developed a heuristic algorithm which is capable of incorporating wide range of prioritization rules. Their algorithm utilizes different combinations of all possible cuts in a smart fashion to obtain an activity schedule that solves the resource critical issues while satisfying a given measure of performance, such as project duration. Using this heuristic resulted in a superior solution compared to approaches which use each priority rule individually. This algorithm is known as Resource Activity Critical Path Method (RACPM) in the literature.