A multi-objective DCP model for bi-level resource-constrained project scheduling problems in grounding grid system project under hybrid uncertainty

Since more elements are involved in the construction projects, the decision making process of Resource-constrained Project Scheduling Problems (RCPSP) cannot be determined by a manager, but multiple level decision makers. This study focuses on the RCPSP in a practical grounding grid system project in Jin’ An Qiao hydropower station, which consider the hierarchical organization structure and hybrid uncertainty environment simultaneously. In this practical RCPSP, the construction contractor is the Upper Level Decision Maker (ULDM), while the outsourcing partner is the Lower Level Decision Maker (LLDM). Considering the operations difficulties and practical decision making process in the RCPSP, a bi-level multi-objective RCPSP model with bi-random coefficients is developed. To deal with the bi-random variables in the model, the Dependent-Chance Programming (DCP) method is introduced and the equivalent crisp model is derived. Subsequently, motivated by the particular nature of model, Bi-level Global-local-neighbor Particle Swarm Optimization Algorithm (BGLN-PSO) is designed to obtain the optimal schedule for grounding grid system project. A practical application is presented to verify the efficiency of proposed bi-level multi-objective RCPSP model and algorithm.