With　the　advantages　of　high　efficiency　and　convenience,　UAV　cluster　combat　has　become　an　increasingly　mainstream　battlefield　method.　Efficient　assignment　of　weapons　and　targets　to　UAV　clusters　can　significantly　enhance　operational　effectiveness,　underscoring　the　importance　of　proper　assignment　of　UAV　missions.　The　conventional　UAV　task　assignment　problem　consists　of　assigning　weapons　and　targets　individually,　which　yields　incomplete　results　and　fails　to　take　into　account　the　mutual　constraints　between　weapons　and　targets.　This　paper　presents　a　mathematical　model　for　a　confrontational　environment　in　a　multi-UAV　cluster　combat　scenario,　incorporating　spatio-temporal　constraints　to　achieve　Simultaneous　Weapon-Target　Assignment　(SWTA).　Furthermore,　this　paper　advances　the　conventional　UAV　task　assignment　problem　by　enabling　the　simultaneous　assignment　of　weapons　and　targets　through　their　integration,　and　achieves　a　more　comprehensive　assignment　outcome　for　UAV　cluster　combat　through　the　utilization　of　genetic　algorithms.　Finally,　a　case　study　with　15　UAVs　and　30　targets　considering　various　weapons　has　demonstrated　that　the　proposed　method　can　improve　the　success　rate　and　efficiency　of　task　accomplishment　in　combat　scenarios.