Genetic algorithm for the resource-constrained project scheduling problem

We consider the resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. We propose a genetic algorithm with two versions of crossovers based on the idea of most rational use of constrained resources. The crossovers uses a heuristic that takes into account the degree of criticality for the resources, which is derived from the solution of a relaxed problem with a constraint on accumulative resources. A numerical experiment with examples from the PCPLIB library has shown that the proposed algorithm has competitive quality. For some examples from the j120 test series the best known solutions were improved and for j60 (50 000 and 500 000 iterations) and for j120 (500 000 iterations) we have obtain the best average deviations of the solutions from the critical path value.