Fast and Near-Optimum Schedule Optimization for Large-Scale Projects

Abstract

Real-life construction projects are large in size and are challenged by many constraints, including strict deadlines and resource limits. In this paper, constraint programming (CP) is used as an advanced mathematical technique that suits schedule optimization problems. A practical CP optimization model has been developed to resolve both deadline and resource constraints simultaneously in large-scale projects. The proposed CP model is much faster than metaheuristic techniques and provides a set of feasible project durations that do not violate resource limits. The paper compares the CP results with several case studies from the literature to prove the practicality and usefulness of the CP approach to both researchers and practitioners. The CP model of this paper could provide solutions within 6.5% deviation from optimum schedules for a large project of 2,000 activities within minutes of processing time. This paper thus contributes to introducing a superior optimization model that is suitable for large-size projects and helps to render schedule optimization a mainstream cost-saving function within commercial scheduling systems.