This study fully considers the cascading effects in the program, constructs a schedule robustness evaluation indicator under the cascading effects of program schedule and quality and proposes an optimization method for program schedule robustness. This study aims to improve the program schedule robustness, thereby enhancing its risk resistance capacity.
Through a dual-methodological approach: (1) Simulation techniques quantify CPs’ cascading effect coefficients, while (2) theoretical derivation calculates unstable penalty costs. The integrated optimization model is empirically validated using Program Z as a case study, combining robustness indicators that capture both fundamental temporal parameters (start/finish time and duration) and multi-stakeholder dynamics (schedule/quality cascading effects).
The proposed model demonstrates superior stability and effectiveness compared to existing methods. Case results confirm that the dual-factor robustness indicators (basic + cascading factors) provide scientifically valid measurements. The solution methodology successfully overcomes previous limitations in handling complex stakeholder interdependencies.
This study provides program managers with feasible solutions to optimize the schedule, aiming to enhance the risk resistance capacity of programs and reduce their losses caused by uncertainties.
This paper considers both quality and schedule simultaneously for the first time, constructs program robustness indicators that take cascading effects into account and establishes a program robustness optimization model based on the indicators. This paper provides new ideas and insights for improving the risk resistance capacity of programs. Theoretically, this study extends the complex systems theory and program management perspective by introducing a dual-dimension robustness framework that integrates quality- and schedule-driven cascading effects. It deepens the understanding of how multi-stakeholder interactions influence program robustness through systemic propagation mechanisms.
