School Economics & Management, Nanjing University of Science and Technology, Nanjing 210094, P. R. CHINA
bState Key Laboratory of Hydraulics and Mountain River Engineering, Sichuan University; Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu, 610065, P. R. CHINA
National Key Laboratory of Air Traffic Control Automation System Technology, Sichuan University; College of Computer Science, Sichuan University, Chengdu, 610065, P. R. CHINA
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.