In　alternative　generation,　reusing　past　experience　is　a　potential　methodology　and　case　retrieval　is　a　primary　step.　In　order　to　improve　the　performance　of　case　retrieval　process,　many　applications　have　used　different　similarity　measurements　and　the　selection　method　for　the　most　suitable　historical　case　to　solve　problems.　Many　investigations　have　shown　that　human　beings　are　usually　bounded　rational　and　their　psychological　behavior　has　certain　influence　on　decision　making.　However,　such　behavior　is　neglected　in　similarity　measurements　and　the　selection　method　can　only　deal　with　the　evaluation　given　by　one　decision　maker　(DM).　This　paper　proposes　a　new　case　retrieval　method　that　combines　similarity　measurement　and　data　envelopment　analysis　(DEA)　model.　A　similarity　measurement　based　on　cumulative　prospect　theory　is　proposed　to　consider　the　DM’s　psychological　behavior.　A　hybridization　of　four　similarity　measurements　is　used　to　generate　a　set　of　similar　historical　cases.　The　DM　evaluates　the　similar　historical　case　set　by　a　pairwise　comparison　matrix.　A　DEA　model　is　constructed　to　get　the　priority　vector.　The　most　suitable　historical　case　can　then　be　picked　out　through　the　case　similarity　and　the　case　priority.　A　case　study　is　finally　introduced　to　illustrate　the　use　of　the　proposed　method.　©　2018,　the　Authors.