Scheduling　problem　widely　exists　in　the　systems　of　resource-sharing,　mainly　in　the　form　of　mixed　integer　programming.　Large-scale　mixed-integer　programming　problem　is　one　of　the　classic　NP-hard　problems　in　the　field　of　computational　science,　which　cannot　be　solved　through　precise　computation　in　general.　Job-shop　scheduling　is　a　major　sub-field　of　scheduling　and　a　key　aspect　of　intelligent　manufacturing.　Aiming　at　the　flexible　job-shop　scheduling　problems　of　multi-products　and　variety　batch,　a　Petri　nets-based　asynchronous　parallel　ant　colony　optimization　is　proposed　with　the　optimization　target　of　minimizing　the　time　consuming　of　manufacturing　cycle.　A　Petri　nets-based　method　of　creating　step-reachability　graph　is　put　forward,　which　is　used　for　construction　of　search　space　of　ant　colony　optimization.　On　the　basis　of　discussing　the　search　mechanism　of　traditional　ant　colony　algorithm,　a　search　method　of　asynchronous　parallel　for　ant　colony　is　presented　based　on　asynchronous　simulation　clock.　A　multi-threaded　control　method　for　update　of　pheromone　is　used.　Simulation　results　show　that　the　multi-threaded　control　method　can　overcome　the　premature　convergence　effectively.　The　proposed　approach　is　illustrated　by　a　case　of　flexible　job　shop　scheduling　for　an　intelligent　manufacturing　system　of　defense　and　security　facilities,　through　which　solutions　of　high　quality　can　be　found　quickly.　In　sum,　the　proposed　optimization　has　obtained　a　good　effect　in　engineering　applications　while　the　validity　of　optimization　has　been　proved.　©　2016,　Science　Press.　All　right　reserved.