Bi-Level Optimization of Resource-Constrained Multiple Project Scheduling Problems in Hydropower Station Construction under Uncertainty

The aim of this paper is to deal with the resource-constrained multiple project scheduling problems (RCMPSP), which consider the complex hierarchical organization structure and fuzzy random environment in the decision making process. A bi-level multiobjective RCMPSP model with fuzzy random coecients is presented by taking into account the strategy and process in the practical RCMPSP. In the model, the project director is considered as the leader in the upper level, who aims to minimize total tardiness penalty of all sub-projects and the consumption of resources. Meanwhile, the sub-project manager is the follower in the lower level, regards the target to minimize the duration of each sub-project. To deal with the uncertainties, the fuzzy random parameters are transformed into the trapezoidal fuzzy variables first, which are de-fuzzified by the expected value index subsequently. A multiobjective bi-level adaptive particle swarm optimization algorithm (MOBL-APSO) is designed as the solution method to solve the model. The results and analysis of a case study are presented to highlight the practicality and eciency of the proposed model and algorithm.