To　improve　the　distribution　performance　of　multiobjective　particle　swarm　optimization　algorithm,an　adaptive　multiobjective　particle　swarm　optimization　algorithm,based　on　the　decomposed　archive,named　AMOPSO-DA,is　developed　in　this　paper.First,an　external　archive　update　strategy,based　on　the　spatial　distribution　information　of　optimal　solutions,is　designed　to　improve　the　searching　ability　of　AMOPSO-DA.Second,an　adaptive　flying　parameter　adjustment　strategy,based　on　the　evolutionary　direction　information　of　each　particle,is　proposed　to　balance　the　exploration　ability　and　the　exploitation　ability.Finally,this　proposed　AMOPSO-DA　is　applied　to　some　multiobjective　optimization　problems.The　experiment　results　demonstrate　that　AMOPSO-DA　can　obtain　well-distributed　optimal　solutions.　©　2020,　Chinese　Institute　of　Electronics.　All　right　reserved.