Various　Industrial　Internet　of　Things　(IIoT)　devices　and　their　compelling　applications　have　witnessed　exponential　growth　over　the　past　few　years.　Compared　to　the　consumer　internet,　the　industrial　IoT　often　faces　tough　communication　latency　boundaries　and　low　packet　loss.　Recently,　time-sensitive　networks　(TSN)　technique　has　been　considered　the　most　promising　solution　to　tackle　these　issues,　providing　deterministic　communication　guarantees　for　time-sensitive　applications.　In　TSN,　to　achieve　bounded　low　latency,　it　introduces　the　Cyclic　Queuing　and　Forwarding　(CQF)　mechanism　to　shape　and　regulate　the　transmission　selection　to　provide　the　protected　transmission　window　for　time-triggered　(TT)　flows.　Currently,　a　considerable　amount　of　literature　has　explored　traffic　scheduling　with　the　CQF　mechanism　in　TSN.　However,　these　methods　ignore　the　impact　of　routing　policy　on　scheduling　optimization.　In　this　paper,　we　design　two　algorithms　to　tackle　the　problem　of　joint　routing　and　scheduling　optimization　with　the　CQF　mechanism　for　TSN.　We　propose　a　TT　flow　sorting　algorithm　(JDPS)　to　measure　the　scheduling　priority　weight　of　each　TT　flow,　which　uses　the　normalization　method　to　calculate　the　weight　based　on　the　flow's　deadline,　period,　and　size.　Then,　we　propose　a　joint　routing　and　scheduling　optimization　with　load　balance　algorithm　(JRS-LB)　to　improve　the　scheduling　success　radio　and　the　network　resource　utilization,　which　jointly　considers　the　injection　time　slot　offset,　scheduling,　and　routing　of　TT　traffic.　The　evaluation　results　mainly　focus　on　the　scheduling　success　ratio,　execution　time,　and　resource　utilization　for　the　proposed　algorithm　compared　to　the　Tabu　and　Naive　algorithms.　Extensive　simulations　indicate　that　the　proposed　JDPS　and　JRS-LB　algorithms　can　improve　the　scheduling　success　radio　compared　with　the　other　algorithms.　IEEE