The　scale　of　heating　system　is　expanding　day　by　day　and　the　structure　of　pipeline　network　is　becoming　more　and　more　complex.　Therefore,　it　is　urgent　for　heating　enterprises　to　establish　accurate　hydraulic　models　of　pipeline　network　to　assist　their　operation　and　management.　The　pipe　roughness　of　heating　pipeline　is　critical　to　hydraulic　models,　but　unfortunately　it　is　however　uncertain.　Thus,　it　is　necessary　to　obtain　the　resistance　coefficient　values　of　pipe　roughness　of　heating　pipeline.　At　present,　the　pipeline　roughness　is　commonly　estimated　with　optimization　calculation　based　on　collected　measurement　data　of　heating　systems.　The　optimization　problem　is　however　multi-dimensional　and　complex　to　solve.　In　this　work,　an　auxiliary　individual　oriented　crossover　genetic　algorithm　(AIOX-GA)　is　proposed　to　optimize　the　problem　of　estimating　the　resistance　coefficient　values　of　pipe　roughness.　AIOX-GA　adopts　a　crossover　framework　and　is　an　auxiliary　individual-oriented　scheme,　which　is　helpful　to　solve　multi-dimensional　problems.　The　performance　of　the　improved　algorithm　is　evaluated　with　simulation　experiments.　The　results　show　that　the　proposed　algorithm　can　accurately　estimate　the　pipeline　roughness　and　effectively　improve　the　identification　accuracy.