With　concentration　on　the　defects　of　ant　colony　algorithm　as　not-high　precision　and　much　iteration　existing　in　the　algorithm　of　multi-task　coalition　problem　(MTCP),　this　dissertation　utilized　the　characteristics　of　quantum　computation　simultaneously　processing　substantial　quanta　in　parallel　to　put　forward　quantum　ant　colony　algorithm　on　MTCP.　First,　it　utilized　quantum　superposition　states　to　give　quantum　code　based　on　Agent,　making　each　Agent　occupy　2　positions　in　the　space;　Second,　in　order　for　the　rotation　angle　to　obtain　proper　size　and　direction,　it　posed　the　self-adaptive　and　corrective　rotation　angle　adjusting　strategy　on　the　basis　of　pheromone;　Finally,　it　gave　ant　algorithm-seeking　strategy　based　on　the　quantum　states　by　monitoring　on　the　quantum　code.　Substantial　simulation　experiments　show　that,　compared　with　existing　algorithms,　this　one　can　not　only　obtain　better　algorithm,　but　also　improve　the　convergence　speed　prominently.