Flexible　job　shop　problem　(FJSP),　known　as　a　well-known　combinatorial　optimization　problem,　is　very　important　in　fields　of　production　management.　An　improved　ant　colony　optimization　(IACO)　is　presented　to　solve　the　FJSP　in　this　paper.　In　IACO,　three　improved　strategies,　transition　rule　with　adaptive　parameters,　crossover　operation　and　pheromone　updating　strategy　with　adaptive　parameters　are　introduced　to　enhance　the　performance　of　ACO.　The　effectiveness　of　IACO　is　examined　by　some　best-known　instances　from　literatures.　Results　show　the　proposed　algorithm　seems　to　be　a　powerful　tool　for　FJSP　compared　with　other　heuristic　algorithms.