Floorplanning　is　an　important　issue　in　the　very　large-scale　integrated　(VLSI)　circuit　design　automation　as　it　determines　the　performance,　size,　yield　and　reliability　of　VLSI　chips.　This　paper　proposes　a　novel　intelligent　decision　algorithm　based　on　the　particle　swarm　optimization　(PSO)　technique　to　obtain　a　feasible　floorplanning　in　VLSI　circuit　physical　placement.　The　PSO　was　applied　with　integer　coding　based　on　module　number　and　a　new　recommended　value　of　acceleration　coefficients　for　optimal　placement　solution.　Inspired　by　the　physics　of　genetic　algorithm　(GA),　the　principles　of　mutation　and　crossover　operator　in　GA　are　incorporated　into　the　proposed　PSO　algorithm　to　make　this　algorithm　to　break　away　from　local　optima　and　achieve　a　better　diversity.　Experiments　employing　MCNC　and　GSRC　benchmarks　show　that　the　proposed　algorithm　is　effective.　The　proposed　algorithm　can　avoid　local　minimum　and　performs　well　in　convergence.　The　experimental　results　of　the　proposed　method　in　this　paper　can　also　greatly　help　floorplanning　decision　making　in　VLSI　circuit　design　automation.　©　2009　Springer-Verlag.