Genetic algorithm for type-2 assembly line balancing

The assembly line balancing problem (ALBP) consists in finding the best assignment of tasks between several workstations. An evenly distribution reduces idle time and therefore results in more efficient production systems. Although several models have been proposed for ALBP, real lines present restrictions that usually violate simplifications assumptions. This paper presents a hybrid genetic algorithm to solve balancing problems with assignment restrictions. Heuristics are dynamically used in the encoding process to reduce search space and to focus the search on promising areas. The hybrid GA is able to obtain solutions close to the optimal (0.79% in average) for the most used dataset in the literature. The presented GA can incorporate equipment or zoning restrictions that might be present in real assembly lines.