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 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 coefficients is presented, taking into account the strategy and process in the practical rcmpsp. in the model, the project director is considered the leader at the upper level who aims to minimize the total tardiness penalty of all sub-projects and the consumption of resources. meanwhile, the sub-project manager, a follower at the lower level, regards the target to minimize the duration of each sub-project. to deal with the uncertainties, fuzzy random parameters are transformed into trapezoidal fuzzy variables first, which are subsequently de-fuzzified by the expected value index. a multi-objective 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 efficiency of the proposed model and algorithm.