The Assembly Line Balancing (ALB) problem is a well-known manufacturing optimization problem, which determines the assignment of various tasks to an ordered sequence of stations. As Genetic Algorithms (GAs) have established themselves as a useful optimization technique in the manufacturing field, the application of GAs to ALB problem has expanded a lot. This paper describes a Generalized Pareto-based Scale-independent Fitness Function Genetic Algorithm (gp-siffGA) for solving ALB problem with Worker Allocation (ALB-wa) to minimize the cycle time, the variation of workload and the total cost under the constraint of precedence relationships at the same time. The results indicated that the...