A　mixed　integer　linear　model　for　selecting　the　best　decision　making　unit　(DMU)　in　data　envelopment　analysis　(DEA)　has　recently　been　proposed　by　Foroughi　[Foroughi,　A.　A.　(2011a).　A　new　mixed　integer　linear　model　for　selecting　the　best　decision　making　units　in　data　envelopment　analysis.　Computers　and　Industrial　Engineering,　60(4),　550-554],　which　involves　many　unnecessary　constraints　and　requires　specifying　an　assurance　region　(AR)　for　input　weights　and　output　weights,　respectively.　Its　selection　of　the　best　DMU　is　easy　to　be　affected　by　outliers　and　may　sometimes　be　incorrect.　To　avoid　these　drawbacks,　this　paper　proposes　three　alternative　mixed　integer　linear　programming　(MILP)　models　for　identifying　the　most　efficient　DMU　under　different　returns　to　scales,　which　contain　only　essential　constraints　and　decision　variables　and　are　much　simpler　and　more　succinct　than　Foroughi＇s.　The　proposed　alternative　MILP　models　can　make　full　use　of　input　and　output　information　without　the　need　of　specifying　any　assurance　regions　for　input　and　output　weights　to　avoid　zero　weights,　can　make　correct　selections　without　being　affected　by　outliers,　and　are　of　significant　importance　to　the　decision　makers　whose　concerns　are　not　DMU　ranking,　but　the　correct　selection　of　the　most　efficient　DMU.　The　potential　applications　of　the　proposed　alternative　MILP　models　and　their　effectiveness　are　illustrated　with　four　numerical　examples.　(C)　2011　Elsevier　Ltd.　All　rights　reserved.