Modified Streamlined Optimization Algorithm for Time-Cost Tradeoff Problems of Complex Large-Scale Construction Projects

Although research on time-cost tradeoff (TCT) problems has been extensively conducted, there are still few applications of TCT optimization methods in the scheduling of projects with practical size and complexity. As a good attempt, a streamlined optimization algorithm has recently been developed for solving TCT problems with a continuous curvilinear activity time-cost relationship. However, the algorithm encounters the difficulties of high memory requirements and computational demand when it is implemented in complex large-scale projects whose networks may involve tens of millions of paths and hundreds of activities. To overcome such difficulties, this study presents a modified version of the streamlined optimization algorithm. Particularly, a new method for identifying critical paths is proposed in the modified algorithm. Also, a modeling problem has been addressed in order to consolidate the theoretical foundation of the algorithm. As illustrated by the experimental examples, the modified streamlined algorithm outperforms the original algorithm and the commonly used genetic algorithm in terms of optimality, robustness, and computational efficiency. This study thus contributes to the development of commercial scheduling software capable of tackling practical TCT problems.