In　the　model-based　diagnosis　method　of　distribution　network　faults,　the　minimum　hitting　set　calculation　has　a　great　impact　on　the　whole　diagnostic　process.　A　new　minimum　hitting　set　algorithm　suitable　for　the　distribution　network　topology　is　proposed　to　improve　the　efficiency　and　accuracy　rate　of　model-based　diagnosis.　The　new　fitness　function　in　the　algorithm　allows　the　particle　iterating　towards　the　minimum　hitting　set　directly.　As　a　result,　the　search　efficiency　for　the　solution　space　is　improved　correspondingly.　A　search　strategy　of　＂feature　learning＂　is　used　to　reduce　the　search　for　unsolved　space.　Analyzing　the　relation　between　analytic　redundancy　relations　of　distribution　network　components,　the　theoretical　basis　and　implementation　method　of　algorithm　stratification　are　put　forward.　The　example　shows　that　the　improved　minimum　hitting　set　algorithm　has　shorter　solution　time　and　higher　accuracy.　Applying　the　improved　minimum　hitting　set　algorithm　to　model-based　diagnosis,　the　efficiency　and　accuracy　of　fault　diagnosis　are　improved.　©　2020,　Power　System　Protection　and　Control　Press.　All　right　reserved.