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

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

Amir Ahrari (University of Maryland, College Park, USA) and Ali Haghani (University of Maryland, College Park, USA)
Copyright: © 2019 |Pages: 16
DOI: 10.4018/IJITPM.2019070102

Abstract

Two scheduling practices are commonly used depending on the availability of resources. When resources are not expensive, activities are scheduled and then resources are allocated until the available resources are exhausted. Then, iterative adjustments are applied to the resource allocation plan and the activities sequence to reach a feasible solution. Conversely, when expensive resources are involved, a resource allocation plan based on the economics of the resource is established and then activities are scheduled accordingly. However, Resource Constrained Scheduling Problems (RCSP) are not solved efficiently with either of these approaches. To find the optimal solution, activity scheduling and resource allocation should be formulated as an integrated optimization problem. Such models become numerically cumbersome for practical size problems and difficult to solve. In this article, a novel mathematical formulation and an efficient solution algorithm are proposed for solving RCSPs. Then, this framework is used for solving a practical problem in the context of the construction industry.
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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.

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