In　recent　years,　frequent　public　emergencies　have　resulted　in　heavy　casualties　and　economic　losses.　In　the　early　stage　of　emergency　rescue,　the　demand　for　emergency　resources　is　strictly　greater　than　the　supply.　As　an　important　part　of　emergency　management,　emergency　resource　scheduling　is　an　important　manifestation　of　its　rescue　value.　At　present,　Many　studies　take　emergency　resource　scheduling　as　a　multi-objective　optimization　problem.　They　focus　on　the　total　emergency　cost　and　does　not　evaluate　the　emergency　resource　allocation　according　to　the　actual　disaster　severity　of　each　emergency　demand　point.　What’s　more,　they　do　not　consider　road　information.　However,　in　actual,　the　condition　of　roads　directly　affects　the　emergency　cost.　To　address　this　problem,　we　proposed　an　effective　emergency　logistics　scheduling　model　based　on　multi-objective　optimization　algorithms.　We　get　road　information　from　spatial-temporal　trajectory　data.　The　research　on　emergency　resource　scheduling　in　this　paper　is　helpful　to　achieve　greater　utility　under　the　condition　of　limited　emergency　resources　and　reduce　the　loss　of　public　emergencies.　©　2018　Association　for　Computing　Machinery.