An　artificial　fish　swarm　algorithm　based　on　Pareto　multi-objective　optimization　is　proposed　for　optimal　sensor　placement　in　structural　health　monitoring.　The　modal　independence,　damage　sensitivity　and　damage　redundancy　are　firstly　utilized　to　establish　the　sensor　multi-objective　optimization　function.　Then　the　rear-end　and　foraging　behaviors　in　the　artificial　fish　swarm　algorithm　are　improved,　and　the　external　file　sets　are　introduced　for　the　centralized　processing　of　the　mutually　non-dominating　solutions　in　the　optimization　process.　The　Pareto　solution　with　the　closest　Euclidean　distance　at　the　ideal　point　is　considered　as　the　final　optimal　solution.　A　planar　frame　structure　is　finally　used　as　a　numerical　study　to　verify　the　proposed　artificial　fish　swarm　algorithm　based　on　Pareto　multi-objective　optimization　for　sensor　optimal　placement.　The　results　obtained　from　the　proposed　method　give　a　fairly　uniform　spacing　for　the　sensor　locations,　and　the　information　obtained　by　the　measurements　is　more　comprehensive,　with　low　redundancy　and　good　mode　independence.　The　damage　detection　results　also　indicate　the　robustness　of　the　proposed　method.　©　2022,　Editorial　Board　of　Journal　of　Vibration　Engineering.　All　right　reserved.