The　problem　of　circuit　partitioning　is　a　key　phase　in　the　physical　design　of　VLSI.　In　this　paper,　we　propose　a　multi-objective　discrete　PSO　(DPSO)　algorithm　for　the　problem　of　VLSI　partitioning.　Moreover,　a　new　strategy　of　heuristic　local　search　is　employed　to　accelerate　the　convergence.　The　main　target　of　this　multi-objective　problem　is　optimizing　the　minimum　cut　and　timing　performance　(delay)　while　area　balance　is　taken　as　a　constraint.　The　fitness　function　of　phenotype　sharing　is　used　to　evaluate　solution　by　both　pareto　dominance　and　neighborhood　density.　The　experimental　results　on　ISCAS89　benchmarks　are　performed　to　validate　the　proposed　algorithm.　Compared　with　genetic　algorithm　(GA)　and　Tabu　Search　(TS)　in　literature　[4],　the　proposed　algorithm　could　obtain　more　markedly　better　solutions　for　bipartition　problem.　©　2010　Springer-Verlag　Berlin　Heidelberg.