If　a　system　is　not　up　to　the　standard　in　an　evaluation,　what　solution　should　be　selected　to　amend　the　system　is　a　subsequent　decision　problem　after　evaluation.　The　subsequent　decision　for　fuzzy　comprehensive　evaluation　is　studied　from　the　perspective　of　economics,　namely,　the　evaluation　threshold　requirements　are　met　at　the　least　cost.　Firstly,　the　models　of　score　cost,　score　unit　cost,　and　improved　cost　are　established.　Based　on　the　three　models,　each　index　score　is　encoded　as　a　genetic　information.　The　genetic　algorithm　is　used　to　iteratively　calculate　an　index　score,　which　could　meet　the　requirements　of　fuzzy　evaluation　score　threshold　with　the　least　improved　cost.　Finally,　the　iteration　process　and　results　are　analyzed,　an　an　index　modification　priority　model　is　established.　When　the　budget　is　tight　or　the　system　is　difficult　to　be　operated,　the　model　could　be　used　to　decide　the　priority　for　modifying　the　indexes.　The　system　reaches　a　set　standard　and　the　modification　sequence　of　the　indexes　through　2000　iterative　calculations　The　proposed　method　can　be　used　for　the　conventional　evaluation,　such　as　gray　evaluation,　extenics　assessment　and　set　pair　analysis.　©　2015,　China　Ordnance　Society.　All　right　reserved.