This paper presents a hybrid schedule generation scheme for solving the
resource-constrained project scheduling problem. The scheme, which is called the Polarized
Adaptive Scheduling Scheme (PASS), can operate in a spectrum between two poles, namely the
parallel and serial schedule generation schemes. A polarizer parameter in the range
between zero and one indicates how similarly the PASS behaves like each of its two poles.
The presented hybrid is incorporated into a novel genetic algorithm that never
degenerates, resulting in an effective self-adaptive procedure. The key point of this
genetic algorithm is the embedding of the polarizer parameter as a gene in the genomes
used. Through this embedding, the procedure learns via monitoring its own
performance and incorporates this knowledge in conducting the search process. The
computational experiments indicate that the procedure can produce optimal solutions for a
large percentage of benchmark instances.