Abstract
In this paper, we consider a bicriteria two-machine flow-shop scheduling problem which is to simultaneously minimize both Cmax and Tmax criteria, and we propose a new genetic algorithm for enumerating all nondominated solutions for this problem. Our algorithm is constructed by incorporating several existing strategies developed for multi-objective optimization problems together with a new strategy which we call seeding strategy that seeds some good individuals in the initial population. We perform computational experiments in order to compare our algorithm with other existing methods.We observe from our computational results that our algorithm produces nondominated solutions very close to exact ones, and outperforms other existing heuristics.
