The proposed approach to the runner-balancing problem evaluates differences in shrinkage among the cavities and uses this direct measure of product quality to balance runner systems instead of the indirect methods traditionally used. The runner-balancing problem was characterized by multiple objectives, which consider both cost and product quality. The resulting multi-objective optimization problem was solved with a multi-objective genetic algorithm. Runner-balancing optimizations varied the diameters and lengths of the runners and the processing conditions. The results suggest that balanced runner systems, which exhibit large differences in cavity pressure profiles, can have lower product costs than systems characterized by similar fill times and cavity pressure profiles. The optimization of the secondary runner lengths and processing conditions also reduced costs significantly. (C) 2004 Society of Plastics Engilieers.