In-network　data　aggregation　in　wireless　sensor　networks　(WSNs)　can　reduce　data　redundancy　in　the　process　of　data　gathering　and　therefore　decrease　energy　consumption.　Since　aggregation　cost　sometimes　can　not　be　neglected　in　some　realistic　applications,　it　is　important　how　to　construct　an　effective　route　strategy　which　optimizes　not　only　communication　cost　but　also　aggregation　cost.　In　addition,　we　further　study　how　to　adaptively　adjust　route　structure　to　avoid　some　nodes＇　premature　death.　To　solve　the　above　problems,　we　introduce　heuristic　algorithms　based　on　discrete　particle　swarm　optimization　(DPSO).　And　the　notions　of　mutation　and　crossover　operators　in　genetic　algorithm　are　incorporated　into　the　discrete　procedure　of　PSO,　which　can　not　only　keep　the　diversity　of　population,　but　also　make　offspring　population　maintain　the　preferable　characteristics.　Experimental　results　show　that　our　algorithms　can　effectively　reduce　energy　consumption　and　trade　off　energy　consumption　and　network　lifetime,　compared　with　other　tree　routing　algorithms.