Multi-objective scheduling optimization for linear megaprojects considering technological innovation

Technological innovation plays a critical role in driving the progress of linear megaprojects, despite being characterized by uncertainty and longtime spans between demand generation and application. To effectively incorporate the expectations of technological innovation time (ET) into construction management, a multi-objective scheduling optimization model is proposed. This model treats duration, cost, and robustness as multi-objectives, using the Linear Scheduling Method (LSM), which is more suitable for linear projects. It incorporates ET as scattered buffers, predicted by the Graphic Evaluation and Review Technique (GERT) network planning method. An improved Nondominated Sorting Genetic Algorithm III (I-NSGA3) heuristic algorithm is employed to obtain the solution. Furthermore, the advantages of the model are examined through algorithm comparison, and sensitivity analysis is conducted to investigate the impact of ET on multiple objectives, as well as to determine the ET threshold for ensuring an optimal scheduling plan. Finally, case studies are presented to illustrate the applicability and effectiveness of the proposed model. The study concludes that when the expected time for technological innovation is less than one-eighth of the duration limit, an optimal schedule that balances cost, time, and robustness can be achieved. However, when the expected time exceeds half of the duration limit, significant schedule delays occur with minimal cost changes.