An　immunization　strategy　based　on　particle　swarm　optimization　is　presented　to　effectively　solve　the　control　of　the　virus　spread　in　the　weighted　scale-free　networks.　Motivated　by　the　idea　of　network　partition,　two　optimization　goals　with　the　sub-network　scale　and　the　sum　of　the　sub-network　strength　are　simultaneously　taken　into　account.　Moreover,　the　mutation　and　the　crossover　operator　of　genetic　algorithm　are　introduced　to　improve　the　population　diversity　and　avoid　the　algorithm　falling　into　a　local　optimal　solution　prematurely.　Simulation　results　show　that　the　proposed　immunization　strategy　has　better　performance　than　the　targeted　immunization　strategy　which　is　generally　considered　to　be　highly　efficient　at　present.　Through　immunizing　the　specified　number　of　nodes,　the　network　can　be　well　divided　into　the　sub-networks　whose　nodes　number　and　sum　of　nodes　strength　are　as　small　as　possible.