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A bicriteria two-machine flowshop scheduling problem is addressed to minimize the number of setups and makespan. The jobs have sequence dependent setup times. Scheduling problems considering either of these objectives are NP-hard. Two multi-objective metaheurisctics based on genetic algorithms (MOGA) and simulated annealing (MOSA) are proposed to find approximations of Pareto-optimal frontiers. The performances of these approaches are compared with lower bounds for small problems. In larger problems, their performance is compared with each other. Experimentations revealed that both algorithms perform very similar on small problems and that MOGA outperforms MOSA in terms of the quality of solutions on larger problems.