A genetic algorithm for Multi-Model Assembly Line Balancing Problem

This paper presents a genetic algorithm for Multi-Model Assembly Line Balancing Problem (mmALB). The chromosome representation of the problem is based on priorities. Stochastic universal sampling is used and elitist selection is adapted to avoid degeneration. A new fitness mechanism is achieved to simultaneously balance the cycle time between stations while smoothing workload between-within stations. Our algorithm is validated by standard single-model ALB at first, then an example of multi-model transmission assembly line is provided, and computational results have shown that our approach can work with mmALB very concordantly.