The　distribution　of　the　case　feature　attribute　weights　directly　affects　the　case　retrieval　result.　Aim　at　improving　the　retrieval　precision,　a　retrieval　method　is　proposed　based　on　group　decision-making　for　optimizing　the　case　feature　attributes　weights.　Firstly,　multiple　groups　of　initial　weights　are　obtained　by　genetic　algorithm.　Then,　the　multiple　sets　of　retrieval　results　produced　by　these　weights　are　optimized　through　group　decision-making　method,　and　the　weights　can　be　dynamic　adjusted　through　the　deviations　between　individual　decision　results　and　group　result.　The　simulation　results　indicate　that　the　proposed　approach　can　fully　excavate　the　potential　knowledge　of　attribute　weights　and　thus　result　in　higher　retrieval　accuracy　in　a　case-based　reasoning　system.　The　PID　adjusting　comparison　experiment　of　typical　two　order　delay　system　verifies　the　effectiveness　of　the　new　method.　©　2012　IEEE.