Solving Resource-Constrained Project Scheduling Problem via Genetic Algorithm

Abstract

The resource-constrained project scheduling problem (RCPSP) is an important and challenging problem in the field of construction management. This paper presents a genetic algorithm (GA) for the RCPSP. The proposed algorithm introduces several changes in the genetic algorithm paradigm, such as a new selection operator to select parents to recombine; a modified two-point crossover operator with a specific crossover order; and a linearly decreasing probability-based mutation operator. The proposed algorithm was tested using standard benchmark problems of size J30, J60, and J120 from Project Scheduling Problem Library (PSPLIB) and compared with 19 state-of-the-art metaheuristics in the literature. The computational results validate that the proposed algorithm is a competitive algorithm for solving the RCPSP.