The genetic algorithm with two point crossover to solve the resource-constrained project scheduling problems

In the last few decades, the resource-constrained project-scheduling problem has become the key of the success of researching project in the enterprises and has become a popular problem type in operations research. However, due to its strongly NP-hard status, the effectiveness of exact optimization procedures is restricted to relatively small instances. In this paper, we present a genetic algorithm (GA), the so called genetic algorithm with two-point crossover (GA2P), for this problem that is able to provide near-optimal heuristic solutions. A full factorial computational experiment was set up using the well-known standard instances in PSPLIB, and the results reveal that the algorithm is effective for the RCPSP.