Minimum　spanning　tree　(MST)　problem　is　of　high　importance　in　network　optimization　and　can　be　solved　efficiently.　The　multi-criteria　MST　(mc-MST)　is　a　more　realistic　representation　of　the　practical　problems　in　the　real　world,　but　it　is　difficult　for　traditional　optimization　technique　to　deal　with.　In　this　paper,　a　non-generational　genetic　algorithm　(GA)　for　me-MST　is　proposed.　To　keep　the　population　diversity,　this　paper　designs　an　efficient　crossover　operator　by　using　dislocation　a　crossover　technique　and　builds　a　niche　evolution　procedure,　where　a　better　offspring　does　not　replace　the　whole　or　most　individuals　but　replaces　the　worse　ones　of　the　current　population.　To　evaluate　the　non-generational　GA,　the　solution　sets　generated　by　it　are　compared　with　solution　sets　from　an　improved　algorithm　for　enumerating　all　Pareto　optimal　spanning　trees.　The　improved　enumeration　algorithm　is　proved　to　find　all　Pareto　optimal　solutions　and　experimental　results　show　that　the　non-generational　GA　is　efficient.　(C)　2007　Elsevier　Inc.　All　rights　reserved.