This article presents a novel alternative subgraphs assembly line balancing problem with resource selection and parallel stations. The model considers both the choice between different process alternatives and the selection of production resources for the various tasks. It also allows parallelization of stations in the balanced line, thereby improving the flexibility of the algorithm. The objective of optimization is to minimize the total cost of the planned line. A genetic algorithm is used for solving the model. To evaluate its functionality, the approach was applied to 486 well-known reference problems. In addition, the reference problems were expanded to create a new set of reference problems that serve as a benchmark for the algorithm's new capabilities. The results show that the presented algorithm is feasible for solving the formulated assembly line balancing problem.