The　application　of　Particle　Swarm　Optimization　(PSO)　on　combinatorial　optimization　problems　is　limited,　and　it　is　due　to　the　continuous　nature　of　PSO.　In　order　to　solve　the　Multiobjective　Permutation　Flowshop　Sequencing　Problem　(MPFSP),　a　Discrete　Particle　Swarm　Optimization　(DPSO)　algorithm　is　proposed.　To　obtain　a　well　approximation　of　true　Pareto　front,　the　phenotype　sharing　function　of　the　objective　space　is　applied　in　the　definition　of　fitness　function.　The　effectiveness　of　the　proposed　DPSO　has　been　analyzed　using　5　problems　with　the　objectives　of　minimizing　the　makespan　and　the　total　tardiness,　and　20　benchmarks　problems　with　the　objectives　of　minimizing　the　makespan　and　the　total　flowtime.　The　result　shows　that　the　proposed　DPSO　can　reach　a　good　approximation　of　true　Pareto　front.