The invention discloses an improved genetic programming algorithm optimization method for resource-constrained multi-project scheduling. The method comprises the following steps: step 1, initializingparameters, a function set and an attribute set; step 2, collecting project set data under different working conditions, and decomposing the project set data into a training set and a test set; step 3, extracting project information in each working condition project set in the training set as training input, extracting a function set and an attribute set as coding bases, and training populations in the improved genetic programming algorithm; step 4, judging whether the maximum working condition number of the training set is reached or not, if so, outputting an optimal solution set in the population, and if not, returning to the step 3 after converting the project set; step 5, testing the optimal solution set output in the step 4 by adopting a test set and a training set. According to the method, the resource-constrained multi-project scheduling problem under the single/multiple targets can be solved, the defect that traditional genetic programming is prone to falling into local optimumis overcome, and the searching and training capacity of genetic programming is improved.