Digital　microfluidic　biochips　(DMFBs),　by　precisely　controlling　and　manipulating　minute　fluids,　have　realized　the　integration,　automation,　and　cost-effectiveness　of　biochemical　experiments　and　are　applied　in　various　fields　such　as　medical　diagnostics,　drug　development,　and　environmental　monitoring.　However,　due　to　the　composition　of　microelectronic　component　arrays,　DMFBs　are　prone　to　electrode　faults,　leading　to　erroneous　biochemical　operations　and,　consequently,　inaccurate　experimental　results.　In　this　paper,　a　test　path　optimization　algorithm　combining　an　improved　grey　wolf　algorithm　and　priority　strategy　is　proposed　to　solve　the　problem　of　an　extended　test　droplet　path　when　DMFB　tests　faulty　electrodes.　By　encoding　the　priority　of　the　electrodes　of　the　DMFB　and　the　paths　between　the　electrodes,　the　test　droplet　routing　is　performed　according　to　the　priority　order.　The　priority　coefficients　are　dynamically　adjusted　using　the　improved　grey　wolf　algorithm　to　shorten　the　testing　path　length.　Experimental　results　demonstrate　that　the　proposed　path　optimization　algorithm　reduces　the　path　length　by　0.45%　to　2.08%　compared　to　the　Eulerian　circuit　method　in　offline　testing,　achieving　the　theoretical　optimum　value,　and　by　4.90%　to　10.53%　compared　to　the　ant　colony　algorithm　in　online　testing.　This　provides　an　essential　foundation　for　accelerating　the　safe　and　reliable　development　of　DMFBs　in　healthcare.　©　2024　IEEE.