ඒߛઔߒႃע
รԼᙀรཚʳ 2003 ڣ 12 ִʳ 191-218
σᏰఀৱᕼਝຟᠦϞᔖҢЅଆʳ
оΙܚσᏰ࣏ٽʳ
ఙ ᫄ ౩*! ԃ נ ᙺ* *! ༲ Ӄ Й* * *! ೆ * * * * ဢ ! ࡌ
ٚ۶ՕᖂඒஃေᦸᑓীೈԱࠠڶݙໂᓵഗ៕ΔᝫؘᏁࠠڶᚨشࢤΔط࣍Օ ᖂඒஃऱᜎயေၦΔૉਢආլٵऱေၦᑑᄷΔᄎףေၦ᧯ߓऱᓤᠧࢤፖച۩ऱ
ܺᣄ৫Δࢬאءઔߒऱؾऱഗ࣍բ৬مऱᑓীၞ۩ኔᢞᚨش։࣫֗൶ಘΔאጥ
ᖂೃψඒஃ֒ωᒤࠏΔٽۊᣂᜤᑇᖕছ֗ VIKOR ऄၞ۩ኔᢞᒤࠏ։
࣫Δאડ᧩ڼᑓীࠠڶ໌ᄅࢤΕᖂࢤ֗ኔ೭ࢤऱԿૹᏝଖΖਚٺඒᖂۯΰߓ ࢬαඒஃᜎயေᦸױەڼᑓীհዌ૿֗ᄷঞΔ܀ᦞૹᚨࠉٺߓࢬࢨᖂೃऱࢤ
֗ᏁޣۖڶࢬլٵΔթ౨ฤٽඒஃᜎயေᦸऱڍցࢤ֗ݙᖞࢤΖᣊۿေᦸࢨਢေ
۷ᣊऱംᠲױܓشۊᣂᜤᑇᖕছ֗ VIKOR ऄࠐᇞެေᦸᄷঞࠠڶլٵૠጩ
ۯऱംᠲΔᄎࠩለటኔࢤऱ࣠֗ለࠋऱ։࣫ᔆΖ
ᜢᗖӷǺεᏢǵ௲ৣϲǵ௲ৣຑ᠘ǵԪᜢᖄኧᏵೀǵVIKOR
*Ҭ೯εᏢࣽמᆅࣴز܌റγғ
**୯ٛࡕഢљзୖᒉߏ
***Ҭ೯εᏢࣽמᆅࣴز܌௲
****Ҭ೯εᏢࣽמᆅࣴز܌௲
ႝηແҹࣁǺ[email protected]
ዺВයǺ2003 ԃ 3 Д 18 Вǹ௦ҔВයǺ2003 ԃ 11 Д 14 В
Bulletin of Educational Research
December, 2003, Vol. 49 No. 4 pp. 191-218
Analysis of the Theoretical Basis and Practical Applicability of a College Teacher’s Achievement Evaluation Model:
The Case Study of a National University in Hsinchu Peng-Ting Chen*! Zon-Yau Lee**
Hsiao-Cheng Yu***! Gwo-Hashiung Tzeng****
A b s t r a c t
Any college teacher’s achievement evaluation model should have a clear theoretical basis as well as being easily applicable. In view of the fact that using different criteria to evaluate college teachers’ achievements will increase the complexity and thus reduce the applicability of an evaluation system, this study subjected the model adopted for teacher promotion by the management school of a national university to empirical analysis and exploration. Fuzzy Related Data Pretreatment and the VIKOR method were applied here, and the innovative, theoretical, and practical value of this model was verified. It was con- cluded that every teaching unit in Taiwan can take this model as a reference, but each department, school, or college would need to decide the relative weight of each criterion according to its own characteristics and needs, thereby promoting the diversification and completeness of teacher’s achievement evaluation. In order to achieve a higher analytic quality, it is suggested that Fuzzy Related Data Pretreatment and the VIKOR method can be employed in similar cases to resolve the problems caused by different counting units.
Keywords: college, teacher’s promotion, teacher’s achievement evaluation, Fuzzy Related Data Pretreatment, VIKOR
*Ph.D. student, Institute of Management of Technology, National Chiao Tung University
**Chief of Staff, Armed Forces Reserve Command
***Professor, Institute of Management of Technology, National Chiao Tung University
****Professor, Institute of Management of Technology, National Chiao Tung University E-mail: [email protected]
Manuscript received: Mar. 18, 2003; Accepted: Nov. 14, 2003
ಥăჰ! ኢ
ഏփՕᖂ༼ࣙඒஃඒᖂፖઔߒհᔆፖᏺၞኙषᄎࣚ೭հࠌࡎΔ݁ૠૡ
ࡳψඒஃေၦᙄऄωΔۖඒߛຝ༇ૹٺՕᖂᏆΕפ౨֗ࢤհฆΔਚࣔૡط ٺՕᖂ۞۩ૡࡳඒஃᜎயေၦᙄऄ֗ေၦᄷঞΖඒஃऱඒᖂΕઔߒΕࣚ೭ֽᄷፖ ՕᖂऱᙄᖂګயஒஒઌᣂΔᐙᖂسޣᖂऱᔆ֗࠹ඒऱᦞܓΔ९ঞᄎᐙഏ ୮ऱԳթֽᄷ֗ᤁञԺΖਚڕ۶ૠՕᖂඒஃᜎயေᦸࠌ౨ฤٽᖂس࠹ඒᏁޣΕ ഏ୮ขᄐ࿇୶ؾᑑΕፖኙषᄎհࣚ೭ፖಥΔਢଖઔߒ֗൶ಘऱᤜᠲΖ
ᖂீٺඒᖂۯຝ։ೣٻඒᖂઔߒ᎖Εຝ։ঞೣٻਐᖄᖂس֗ઔ ߒ᎖Εຝ։ঞ᎖ܗᖂسፖீ؆ᤁΕຝ։ঞ᎖ᖄᖂسፖֆ٥ਙ֗ֆ 墿೯Δਚڇ৬م֗ૡࡳඒஃᜎயေᦸᑓীΔࠡေᦸᄷঞऱૹࢤᚨ༇ૹ ٺඒᖂۯඒஃऱऄ֗ᎁवΔթ౨ฤٽඒᖂۯऱٚ೭֗ᏁޣΖඒஃᜎயေᦸ ΰေၦΕေ۷αऱ࣠ຏൄشࠐ܂ඒஃ֒ᔢ֗ٚشࠉᖕΔլᔞᅝऱඒஃᜎயေ
ᦸΰေၦΕေ۷αऱֱऄΔ᎘ঞທګᖂீඒᖂᇷᄭլᅝࠌشΕೣᖄඒஃऱඒᖂֱ
ٻΕᖄીඒஃઔߒ؈װૹ֨Εא֗ࣚ೭ႈؾደྤૹរΔૹঞທګඒஃኙᖂீ؈ඨ
֗ࠃᄐՂขسྤԺტΔၞۖທګඒᖂᔆ܅ᆵΔඒஃዊᥩტ૾܅Δא֗ઔߒ౨Ժ ፖࣚ೭ᄷֽᄷྤऄ࿇ཀΔڂڼ֧شٺඒᖂۯࢤ֗ඒஃऱᨠរΔࠐૡࡳᔞࡵױ
۩ඒஃᜎயေᦸΰေၦΕေ۷αᙄऄΔਢଖઔߒ֗൶ಘऱᤜᠲΖ
ءઔߒؾऱഗ࣍բ৬مऱᑓীၞ۩ኔᢞᚨش։࣫֗൶ಘΔאጥᖂೃψඒஃ
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᧩ءઔߒᑓীࠠڶ໌ᄅࢤΕᖂࢤ֗ኔ೭ࢤऱԿૹᏝଖΖ
ڇઌᣂ֮፦ႃऱመ࿓խΔ࿇ഏΕփ؆ಾኙඒஃᜎயေၦ࿇।ऱ֮ີৰڍΔ Օڍ൶ಘխඒஃေᦸࠫ৫Εૹࢤ֗ඒஃᜎயေၦऱᚌរΖڕܦፖഘΰ2002α ᓵ࣫ભഏףڠ San Bernardino ᖂඒஃေᦸऱۥΙܦᕻڕΰ2000α൶ಘඒஃய ౨ტհփො։࣫ΙᑛၺඒΕ്ᐚᔲΰ1993α൶ಘඒஃေᦸᑓڤΙܦਙሒΰ2001aΔ
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ኙݺഏऱඔقΖ൶ಘՕᖂඒஃေᦸऱ֮ີΔڕ׆ഏࣔΕݳΰ1994α൶ಘցཕ Օᖂඒஃᜎயᑻᚐࠫ৫Δࠀᎅࣔڼࠫ৫ਢআګցཕՕᖂڇߏمՕᖂೃீေᦸխټ
٨ছૄऱڂΔᖂீඒஃፖࠫ৫ऱૠΔ܀ਢڇᑓী৬م৵ࠀآኙေᦸᄷঞਐ ᑑၞ۩ኔᢞ։࣫ΙᔤᤌΕ׆֮խΕᄘි墾֗ᆺدఇΰ2000α൶ಘഏمխ՞Օᖂ ጥᖂೃඒᖂᜎயေၦࠫ৫Δཚඨ༼נᔞᅝױ۩հψඒᖂᜎயေၦߓอωΔאᒔঅ
ေᦸ౨ሒࠩֆؓࢤ֗ড়ᨠࢤΔڼઔߒᓳऱរڇ࣍ം࠴ئ᧯ႛጥᖂೃऱஃ سۖڶயڃگം࠴መ֟ΰႛ 16 ٝαΔᐙઔߒګ࣠հױ۩ࢤ֗ז।ࢤΖഏփՕ ຝ։ᣂ࣍ඒஃေᦸऱ֮ထૹڇࡳࢤऱઔߒΔࢨਢഏ؆ඒஃေᦸࠫ৫հֺለᎅ
ࣔΔຘመኔᢞ։࣫৬مေᦸᑓীऱ֮Δࠀኙ࣍ေᦸਐᑑऱၦ֏։࣫
֗ᦞૹऱઔߒΖ
ഏ؆൶ಘඒஃေᦸऱ֮ץਔ Guskeyΰ1981αૠψᖂسګ༉ം࠴ωΔאڂ
ై։ֱ࣫ऄवඒஃኙᖂسᖂᄐګפፖ؈ඓࠠڶຂٚΙChapman ፖ Hutcheson ΰ1982αൕඒஃᄐسෑፖᠦߡ৫ᨠኘΔ࿇ඒஃᠦऱڂፖඒᖂݾ౨֗ᜎ யऱ۞ݺေࡳڶᣂΙGibson ፖ Demboΰ1984αᒳ፹Աψඒஃய౨ᘝၦ।ωΔࠀط ኔᢞ։࣫խᢞࣔࠡױ۩ࢤΙDembo ፖ Gibsonΰ1980αڇᖂீ۞ݺګ९ऱઔߒխਐ נΔ୮அᛩቼΕ୮அહནΕࢨ୮९ऱᐙԺ؆ڇڂైᄎᐙඒஃऱᜎயΙDivi ΰ1987αڇקᢅࠐڠ܂ඒஃᜎயေ۷ऱઔߒΙGuskeyΰ1988αڇඒஃய౨Ε
۞ݺრᢝፖዌ໌ᄅऱޏߜઔߒխ༼ࠩࠠໂய౨ტऱඒஃױא࠰ܗڍᑇᖂسऱ ᖂΙWoolfok ፖ Hoyΰ1990αڇඒஃய౨ေ۷ઔߒխΔᒳ፹Աඒஃய౨ტၦ।Ι
Scrivenΰ1995αঞ്אඒஃऱԫຂΕࡳՠ܂ຂΕא֗ࡳൣቼऱຂ
Կृࠐ܂ඒஃေᦸऱዌ૿ΙDeemer ፖ Minkeΰ1999αڇᓳඒஃඒᖂய
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ഏ؆ᣂ࣍ᜎயေᦸऱ֮ൎᓳඒஃፖေᦸᑓী֗ᄷঞऱ৬مΔڶܗ࣍ඒஃ ᜎயᔆऱ༼ࣙፖေᦸࠫ৫ऱച۩Ζءઔߒ፦ႃΕᖞፖ։࣫ഏփ؆ڶᣂ࣍ඒஃ ᜎயऱઌᣂ֮Δ៶א᠖堚ψඒஃᜎயωऱᄗ࢚ΕᏝଖΕፖૹࢤᤜᠲΔࠀط ݺഏՕᖂૡࡳඒஃေᦸ֗ေၦհؾऱΔូנՕᖂඒஃᜎயေၦࢨေᦸᚨץਔඒ ᖂΕઔߒ֗ࣚ೭ԿՕଡዌ૿֗ 15 ႈေၦᄷঞΔאڼࠐ৬مՕᖂඒஃᜎயհေᦸᑓ
ীΔࠡڻᆖطኔᢞ։࣫ࠐޣေၦᑓীխٺᄷঞհઌኙૹࢤΖඒஃᜎயေၦܛ ਢኙඒஃڇඒᖂΕઔߒ֗ࣚ೭Կֱ૿հ।אၦ֏ऱֱڤᏝଖऱܒឰΖ
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։࣫ऄࢬ፹܂ऱം࠴Δڃگ 290 ٝΔڬೈྤயം࠴֗آሒԫીࢤᛀࡳऱം࠴Ζڶ யം࠴ٽૠ 255 ٝΔڶயം࠴ڃگሒ 63.4%Ζ
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ֱऄऱࢤΙรᆥᆏءઔߒᒤࠏૠᎅࣔΙรٔᆏၞ۩ኔᢞ։࣫Εᒤࠏᚨش֗
ಘᓵΙรຬᆏᓵፖ৬ᤜΖ
෮ă̂ጯିरᒻड़ෞᝥ͞ڱ̈́
ءᆏڇ൶ಘഏփՕᖂඒஃေᦸֱऄ֗ቤေᦸऱᄷঞΔรԫ՛ᆏᎅࣔՕ ᖂၞ۩ඒஃေᦸऱؾऱΕࠡڻ։࣫ඒஃေᦸፖඒஃ֒ፖٚشऱᣂএΕඒஃေᦸ
ֱऄΕඒஃေᦸࢨေᐉऱႈؾዌ૿֗ᦞૹΔ່৵ၞ۩ಘᓵ։࣫Ζ
ʙă˃ደїࣱඟᜦڟάڟ!
Օᖂඒஃवᢝऱ໌ທृ֗ႚृΔຘመጻᎾጻሁലઔߒګ࣠ᆖطඒᖂຜஉ
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ഏփ؆ٺՕᖂၞ۩ඒஃေᦸऱؾऱΔਢԱ༼ࣙඒᖂΕઔߒፖࣚ೭ऱֽᄷΔ
៶אᏺൎٺՕᖂऱᤁञ౨ԺΔ࠹ေᦸऱኙွຏൄץਔᄅၞඒஃΔא֗آ֒ඒছ հ೫ඒΕܗඒ֗ᝑஃΔࠡေᦸ࣠ԫਢެࡳඒஃ֒ࢨᆤشհࠉᖕΖਙ एՕᖂΰ2002αڇψඒஃഗءᜎயေၦᙄऄωࡳඒஃေၦآຏመृΔլ༼נ
֒ΔԶڣآຏေၦڣየնԼᄣᆖመᐉᤜᖲࠫঞױאլղᥛᆤΖፕՕᖂΰ2002α ψඒஃေ۷ᄷঞωΔᒤᝑஃ֗ܗඒေၦآຏመृլ༼נ֒Δᓤေսآຏ መհඒஃΔᆖԿ్ඒေᄎᐉᤜ৵ঞᙄլᥛᆤࢨᇞᆤ࿓ݧΕ೫ඒေၦآመृঞ լ༼נ֒ΖٌຏՕᖂΰ2000αψඒஃေၦᙄऄωխࡳᄅᆤհ೫ඒΕܗඒ
֗ᝑஃڇࠩٚքڣփΔؘႊຏመ֒Δܡঞ࣍รԮڣದլղᥛᆤΙցཕՕᖂ ΰ1999αψᄅၞඒஃᥛᆤေၦᙄऄωΔՈᒤറٚ೫ඒΕܗඒ֗ᝑஃڇรԮ ڣսآຏመေၦհඒஃڇรԶڣঞլղᥛᆤΖፕஃᒤՕᖂΰ2002αψඒஃေᦸᄷ ঞωΔᒤܗඒ֗ᝑஃΔૉآຏመေᦸृঞլղᥛᆤΖՂ૪ٺՕᖂඒஃေᦸ ΰေၦΕေ۷αᙄऄ֗ࡳΔױवඒஃေᦸፖඒஃ֒֗ٚشڶऴ൷ᣂএΔڂ ڼ৬مԫױၦ֏Εড়ᨠΕֆؓऱඒஃေᦸᑓڤΔᐙඒஃᦞ墿ሰΖ
ʭăࣱඟᜦ̟ٲ!
LoupΕGarlandΕEllett ፖ Ruguttΰ1996αࠉᖕભഏඒஃေᦸኔ೭ᓳઔߒ
ΰTeacher Evaluation Practices SurveyαΔ࿇ඒஃေᦸऱֱऄࠉݧඒஃإڤᨠ ኘΕॺإڤᨠኘΕඒஃ۞ݺေᦸΕඒஃᚾூေᦸΕٵᕦေᦸΕᖂسေᦸΔא֗
ྒྷ᧭ΖᔤᤌԳΰ2000αലေᦸֱڤូᖂسေᦸΕ۞ݺေᦸΕٵᕦေ
ᦸΕ۩ਙေᦸΕ࠴ࡲေᦸΕറ୮ေᦸքᣊΔࠀࡳᆠքᣊေᦸհփ୲Εᚌរ֗ૻࠫΖ
Darling-HammondΕWise ፖ Peaseΰ1983αᖂृڃઌᣂ֮ਐנඒஃေᦸץਔ
ඒஃජᓫΕ౨Ժྒྷ᧭Εၴ൷ྒྷၦΕඒᨠኘΕᖂسေᦸΕٵᕦյေΕᖂسᖂګ
༉ေᦸΕ۞ݺေᦸԶጟֱऄΖء֮ಾኙඒஃ۞ݺေᦸΕᖂسေᦸඒஃΕඒஃٵᕦ
ေᦸΕ۩ਙေᦸΕറ୮ေᦸնጟေᦸֱऄၞ۩ᎅֺࣔ֗ለΖ )Ι*ఀৱՌרຟᠦ!
Harrisፖ Hillΰ1982αᎁඒஃኙ۞աऱඒᖂΕઔߒፖࣚ೭ࠠڶ່ࠥऱᛵᇞΔ
ᆖطփઊፖኔᎾऱᆖ᧭Δඒஃ౨ജኙ۞աऱ۩।ԫଡڶயऱေ۷Ζ܀ਢඒ ஃԱ֒ΕᥛٚΕᆤشڂΔױ౨ᄎࠌ۞ݺေᦸऱֱऄլജড়ᨠΖ
)Π*Ᏸҡຟᠦఀৱ!
ᢥګᖂسေᦸඒஃृᎁᖂس࠹ඒߛऱড়᧯Δڂڼᚨᇠطড়᧯ၞ۩ඒᖂய
࣠հေᦸΙא֗ط࣍ᖂسऴ൷൷࠹ඒஃऱඒᖂΔڂڼᔞٽಾኙඒஃၞ۩ေᦸΖ֘
ኙृᎁᖂسᄎڂ۞ߪኙᖂઝհᘋᔊΕ౨ԺፖೣړऱլٵΔۖኙඒஃທګೣߠΔ ᖂسՈᄎኙᣤऱඒஃړტΔۖᖂسኙ࣍ඒஃհઔߒറᄐፖࣚ೭ՠ܂آ౨
ԵᛵᇞΔڂڼᎁᖂسլࡵေᦸඒஃΖ )έ*ఀৱӣᏔຟᠦ!
طඒஃٵᕦࠐေᦸઌለࠡהေᦸֱڤޓറᄐࠠڶ৫ΔՈױᖿ࿇ٵᕦઌ յٌੌಘᓵ֗ઌյᚐΙ܀Ոױ౨ඒஃઌյᥨࢨઌյ᎘ီඈᚲऱࠟᄕေᦸ
࣠Δ࣐ᐙඒஃڇீ٥ٵઌࢨٽ܂Ζ )Ѳ*ࢇຟᠦ!
۩ਙေᦸطٺ్۩ਙጥ֗ေᐉࡡᄎၞ۩ေᦸΔຏൄױ։Կ్Կᐉေᦸ ΰߓࢬ్Εೃ్Εீ్αΔឈױᝩ܍ط֟ᑇٵᕦေᦸऱរΔ܀ਢط࣍ೃ్ፖீ్
ေᐉࡡᄎኙߓ్ඒஃᛵᇞڶૻΔٍױ౨റᄐေᦸ౨ԺΖ )Ϥ*டড়ຟᠦ!
റ୮ေᦸ່ᔞࡵေᦸඒஃհઔߒګ࣠Δط࣍ေᦸृ݁࠹ေᦸृઌٵറᄐᏆ
֗ైڶټඨऱᖂृᖜٚΔᛵᇞඒஃଡԳറᄐઔߒᏆհထ܂ፖګ࣠Δڂڼေᦸ ऱ࣠ለࠠֆॾԺ֗ড়ᨠࢤΖ܀ط࣍ઌٵᏆհඒஃڼࡺ࣍ᤁञऱچۯΔڂڼ ױ౨ທګψ֮Գઌ᎘ωऱൣउΔڼ؆റ୮ေᦸՈլݙ٤ᔞٽေᦸඒஃհඒᖂᔆ ፖࣚ೭ֽᄷΖ
)ϲ*ω๖!
ጵᖞՂ૪նጟေᦸֱऄհᚌរፖࢤΕەઌᣂ֮Δא֗ٺՕᖂؾছբ ආشऱေᦸΰေၦΕေ۷αֱऄΔԱሒࠩေᦸऱড়ᨠࢤЯֆؓࢤΕٽீ೭հ ؾᑑΕച۩ေᦸհயΕݙᖞ֗٤૿ࢤΕඒஃ൷࠹࿓৫֗ඒஃ۞࿓৫քᣊႈؾ
ၞ۩ֺለΔڕ। 1ΖਚױवေᦸՕᖂඒஃլ౨ႛشԫጟֱऄΔᚨٽࠌشຍն ጟֱڤΔ܀ؘႊڶൕ։ܑΔڕඒஃေᦸૹរڇൎᓳေᦸࠫ৫ऱড়ᨠࢤЯֆؓࢤΔ ঞא۩ਙေᦸ֗റ୮ေᦸΔࠡהေᦸֱऄ᎖Ιඒஃေᦸૹរڇൎᓳฤٽீ
೭࿇୶ؾᑑΔঞאඒஃٵᕦေᦸ֗۩ਙေᦸΔࠡהေᦸֱऄ᎖Ιඒஃေᦸ ૹរڇൎᓳച۩ய࿓৫Δঞאඒஃ۞ݺေᦸ֗۩ਙေᦸΔࠡהေᦸֱऄ
᎖Ιඒஃေᦸૹរڇൎᓳݙᖞ֗٤૿ࢤΔঞאඒஃ۞ݺေᦸ֗ඒஃٵᕦေᦸΔ
ࠡהေᦸֱऄ᎖Ιඒஃေᦸૹរڇൎᓳඒஃհ൷࠹࿓৫Δঞאඒஃ۞ݺေᦸ֗
ඒஃٵᕦေᦸΔࠡהေᦸֱऄ᎖Ιඒஃေᦸૹរڇൎᓳඒஃ۞࿓৫Δঞ אඒஃ۞ݺေᦸ֗ඒஃٵᕦေᦸΔࠡהေᦸֱऄ᎖Ζ
ے1! ˤࣱႍඟᜦ̟ٲ˞̨ྲྀے
άƝඟᜦ̟ٲ ࣱьӨඟᜦ ደΡඟᜦࣱ ࣱϣዔඟᜦ їއඟᜦ ટࣜඟᜦ
ড়ᨠࢤЯֆؓࢤ ܅ խ խ
ฤٽᖂீ࿇୶ؾᑑ խ խ ܅
ച۩ய࿓৫ ܅ խ խ
ݙᖞ֗٤૿ࢤ խ խ ܅
ඒஃ൷࠹࿓৫ ܅ խ խ
ඒஃ۞࿓৫ խ ܅ խ
!
Ͳăࣱඟᜦά!
ඒஃေᦸᜎயႈؾጵᥦፖەݺഏՕᖂऱඒஃေᦸΰࢨေၦαᙄऄፖေ
ᦸᄷঞΔץਔඒᖂΕઔߒ֗ࣚ೭ԿՕႈΖፕஃᒤՕᖂΰ2002αඒஃေᦸᄷঞխΔ ඒᖂዌ૿խץਔඒᖂழᑇٽഗءࡳΕඒᖂေᦸΕਐᖄᖂسᖂઔߒհᜎயΕ
ࠡהඒᖂࠃႈΙઔߒዌ૿խঞץਔᖂᓵထΰࢨ܂Ε୶ዝઌᣂᇷறαΕઔߒૠΕ ઔߒᑻᚐΙࣚ೭ዌ૿խץਔீփࣚ೭֗ீ؆ࣚ೭Ζ׆ഏࣔ֗ݳΰ1994α৬م ඒஃᜎயᑻᚐࠫ৫ᑓڤխΔץਔඒᖂΕઔߒΕࣚ೭ԿՕေ۷ዌ૿Δڇࠡᑓীխല ඒᖂา։ඒᖂ๛Εඒᖂኪ৫Εඒᖂֱऄፖݾ؏֗ᓰ࿓փ୲Ιۖઔߒঞץਔ
ᑻΰඒߛຝࢨഏઝᄎհᖂઔߒᑻ֗ࠡהᖂઔߒۯհᖂᑻαΕᓵ֮࿇।ΰA ᣊཚעΕB ᣊཚע֗ᄎᤜᓵ֮αΕૠΰኔ೭ࢤૠ֗ᖂࢤૠαΙۖࣚ೭ ঞץਔᖄஃࣚ೭֗۩ਙࣚ೭ΰףீփࡡᄎΕᖂ։ఄඒᖂፖ৬ඒٽ܂ፖ࿓৫Ε ኔ᧭ቤጥΕਐᖄᖂسኔ֗ࠡהߓࢬࣚ೭αΖፕՕᖂጥᖂೃΰ2002αࠉ ᖕፕՕᖂඒஃေ۷ᄷঞΔࠐૡࡳඒஃ֒ေᐉᙄऄΔࠡᐉுփ୲ՈץਔઔߒΕ ඒᖂΕࣚ೭ԿႈΔઔߒګ࣠Ծา։ᆖೳټᐉհᖂཚעᓵ֮Εآᆖೳټᐉ
հᖂཚעᓵ֮Εᆖೳټᐉհᖂಘᓵᄎհᓵ֮Εࠡהᖂಘᓵᄎհᓵ֮Εᖂ
റ֗ࠡהΙඒᖂګ࣠ঞץਔطᖂீอԫച۩հඒᖂေᦸ࣠Εᖜٚཚၴ
ࢬၲհᓰ࿓ΕඒઝᒳထΕਐᖄጚ໑Փᓵ֮Εࠡהፖඒᖂڶᣂհګ࣠Ιࣚ೭ګ
࣠ץਔףீࢨೃհࡡᄎΕഏփ؆ထټհཚעፖᒳᙀՠ܂ઌᣂृΕࠡהፖࣚ೭ ڶᣂհՠ܂Ζᚵ֒ඒृࠡەေᦞૹֺࠏઔߒ 70%Εඒᖂ 20%Εࣚ೭֗
ࠡה 10%Ιᚵ֒೫ඒृࠡەေᦞૹֺࠏઔߒ 80%Εඒᖂ 15%Εࣚ೭
֗ࠡה 5%ΔڕڼױवፕՕጥᖂೃൎᓳૹီඒஃऱઔߒګ࣠ΖٌຏՕᖂ ΰ2002αጥᖂೃඒஃေᐉ܂ᄐਜ۩าঞΔร 11 යૡೃඒေᄎေၦૹរઔߒ
֗ඒᖂࠟՕႈΰܶࣚ೭αΔࠡխ֒ܗඒઔߒֺૹ 40%Εඒᖂ 60%Ι֒
೫ඒઔߒֺૹ 50%Εඒᖂ 50%Ι֒ඒઔߒֺૹ 60%Εඒᖂ 40%Δ
ࠟႈ։ᑇؘႊሒࠩየ։հ 75%թฤٽೃ్ေᄎං౺֒ᑑᄷΖፖፕՕጥᖂೃઌ
ֺΔٌՕጥᖂೃૹီඒᖂհֺૹנڍΙڼ؆Δ֒ඒઔߒֺૹֺ֒೫ ඒΔڼፖፕՕጥᖂೃઌ֘Ζ
ˤăਆባ˷ٙ!
Օᖂၞ۩ඒஃေᦸਢԱ༼ࣙඒᖂΕઔߒፖࣚ೭ԿՕዌ૿ऱֽᄷΔࠀཚඨឩ ՕٺՕᖂऱு֨Ꮭଖ֗ᤁञԺΖڼ؆Δඒஃေᦸፖඒஃ֒֗ٚشڶऴ൷ᣂএΔ ڂڼ৬مԫױၦ֏Εড়ᨠΕֆؓऱඒஃေᦸᑓڤΔਢଖԵઔߒऱᤜᠲΖေ
ᦸՕᖂඒஃլ౨ႛشԫጟֱऄΔᚨٽࠌشٺጟֱऄΔေᦸඒஃऱֱऄࠉᖕေᦸ Ꮑޣ္֗ޣؘႊൕڶܑΖඒஃေᦸᜎயႈؾጵᥦፖەݺഏՕᖂऱඒஃေ
ᦸΰࢨေၦαᙄऄፖေᦸᄷঞΔץਔඒᖂΕઔߒ֗ࣚ೭ԿՕႈዌ૿ΔޢՕႈዌ૿
ࢬץਔऱาႈ֗ૹរঞڶլٵΔءઔߒቫᇢᇞެڼԫംᠲΔࠀലઌᣂ֮ઔߒ
࣠֗ەٺீေᦸඒஃᙄऄΔ܂৬ዌءઔߒᑓڤऱഗ៕Ζ
ણăࡁտ͞ڱྻϡ̈́ᄲځ
ඒஃᜎயေᦸᑓী৬مᏁޣኔࠏ։࣫ழΔؘႊەၦటኔᑇᖕᇷறז।ࢤ֗ࡌ
ࢤΔ֠ࠡڇᑇᖕᇷற᠏ངؘ֗ႊ౨ડ᧩ေᦸऱড়ᨠࢤ֗ڶயࢤΖءᆏ൶ಘ ψۊᣂᜤᑇᖕছωڇᑇᖕᇷற᠏ངऱֱڤ֗ࢤΔ౨ᇞެլٵေᦸᄷঞ ૠጩۯऱംᠲΙא֗ڕ۶ሎشڍᄷঞެऱ່ࠋ֏ඈݧֱऄ-VIKORΔא܂Հ ᆏ։࣫ᚨشऱᓵഗ៕Ζ
ʙăиᘰᒒᆵጃ܉୩!
ພᔃፖܦዧႂΰ1998αᎁڇۊᣂᜤ։࣫խΔᑇᖕᇷறऱᒤ၏መՕࢨ ഗᄷၦመՕழΔᄎࠌਬࠄڂऱ܂ش࢙ฃΔۖૉਢᑇᖕᇷறխٺڂऱ ؾᑑֱٻլԫીழΔۊᣂᜤ։࣫Ոױ౨ᄎທګլإᒔऱ࣠Δຍழݺଚؘႊኙᖞ
ิᑇᖕᇷறၞ۩ᑇᖕছऱᖞΖױਢႚอऱᑇᖕᇷறছࠀլݙ٤ਢᒵࢤऱ᠏
ངΔڂڼױ౨ᄎທګᑇᖕᇷறऱ؈టΔא۟࣍ڇᣂᜤࢤ։࣫ऱ࣠ᄎፖࠃኔڶࢬ נԵΔ۟ڶࠄࡳऱழଢᝫᄎທګᑇᖕᇷறխऱਬࠄႈؾ᧢ྤऄࡳᆠΖ
ࢬאᅝݺଚუބנԫᆢࠃٙխΔٺଡࠃٙኙਬࡳࠃٙխऱᣂᜤࢤΔ܀ਢ ݺଚࢬ౨ࠩऱᇷறၦઌᅝڶૻழΔۊᣂᜤ։࣫ਢઌᅝլᙑऱֱऄΖࠡਢ٣ኙᖞ
ิᑇᖕᇷறၞ۩ᑇᖕছऱᖞΔאࠌ٤ຝऱᑇᖕᇷறຟ౨ജየߩױֺለࢤΔܛᑇ ᖕᇷறխऱޢଡցైຟؘႊየߩאՀԿଡයٙΚ
ྤڂڻࢤΰNormalizationαΚᑇᖕᇷறऱڂຟ᥆࣍ٵᣊীΙ
్ࢤΰScalingαΚᑇᖕᇷறխऱଖ݁᥆࣍ٵ్Ι
ٵ్ࢤΰPolarizationαΚᑇᖕᇷறխऱڂ༴૪ᚨٵֱٻΖ
ڼጟ։ֱ࣫ऄլ܀ലᑇᖕᇷறխࢬڶऱଖ٤ຝຟ᠏ངګ 0 ࠩ 1 հၴऱᑇΔࠀ ނࢬڶऱڂऱؾᑑຟᓳᖞګඨՕΔۖᝫլᄎࠌᑇᖕᇷறٺڂऱᇷಛז।؈
టΔٵழՈլᄎڶྤऄࡳᆠऱൣݮ࿇سΔՈ౨ᇞެլٵေᦸᄷঞૠጩۯऱംᠲΖ
ພᔃፖܦዧႂΰ1998αਐנΔڶ m ิᑇᖕᇷற ( ),x k ii =1, ...,m,ʳ 1, ...,
k = nΔࠀڶx k i0( ), =1...mەᑇᖕᇷறΔޣٺิᑇᖕᇷறፖەᑇ ᖕᇷறհᣂᜤ৫։࣫Ζଈ٣ױലࢬڶऱᑇᖕᇷறᆖᑇᖕছ৵Δ٦ല m ᑇᖕᇷ றዌګԫଡ m × n ऱఢೄ XΖྥ৵ലఢೄ X ऱޢଡ٨ຟ྇װەᑇᖕᇷறࠀ࠷
ኙଖ৵ዌګԫଡఢೄϦΖࠡխఢೄϦխऱٺଡցై।قŔ0j( )k Δ່Օऱցై
ŔmaxΔ່՛ऱցైŔminΖࡳᆠԫଡۊᣂᜤᙃᢝএᑇ ξ Δਢԫଡտ࣍ 0 ፖ 1 հၴऱᑇΖঞۊᣂᜤএᑇࡳᆠΚ
min max
0
max
γ( ( ), ( )) ξ
( ) ξ
j
oj
x k x k
k
= +
+
Ŕ Ŕ
Ŕ Ŕ ... (1)
ۖޢଡᑇᖕᇷறፖەᑇᖕᇷறऱۊᣂᜤ৫ঞࡳᆠΚ
0 0
1
γ( , )j 1 n γ( ( ), ( ))j
k
x x x k x k
n =
= ∑ ... (2)
אࠉᖕᑇᇷறऱࢤΔא֗ࠡז।ऱრᆠΔലࠡᑇᖕᇷறᔞᅝऱ᠏ང
֗ᓳᖞΔᒵࢤᑇᖕছऄࠉய࣠ྒྷ৫ױ։ඨՕᑇᖕΕඨ՛ᑇᖕΔא
֗ඨؾᑇᖕԿጟᣊীΖ )Ι*ఖσኵᐃ౩!
ᅝေᦸࢨ։࣫ᑇᖕᇷறਢאყՕყࠋழΔঞආشψඨՕᑇᖕωֱڤࠐ
ၞ۩ᑇᖕᇷற᠏ངΔࠡխmax[xi(0)( )]k ।قਬԫᑇ٨ࢨਢءઔߒඒஃေᦸᑓীհਬ
ԫᄷঞΰီᏁޣۖࡳαऱ່ՕଖΔۖmin[xi(0)( )]k ।قᇠᑇ٨ࢨਢءઔߒඒஃေᦸ ᑓীհਬԫᄷঞΖࠡᑇᖕֆڤڕՀΚ
(0) (0)
*
(0) (0)
( ) min[ ( )]
( )
max[ ( )] min[ ( )]
i i
i
i i
x k x k
x k
x k x k
= −
− ...(3) )Π*ఖωኵᐃ౩!
ᅝေᦸࢨ։࣫ᑇᖕᇷறਢאყ՛ყࠋழΔঞආشψඨ՛ᑇᖕωֱڤࠐ
ၞ۩ᑇᖕᇷற᠏ངΔࠡխmax[xi(0)( )]k ।قਬԫᑇ٨ࢨਢءઔߒඒஃေᦸᑓীհਬ ԫᄷঞΰီᏁޣۖࡳαऱ່ՕଖΔۖmin[xi(0)( )]k ।قᇠᑇ٨ࢨਢءઔߒඒஃေᦸ ᑓীհਬԫᄷঞΖࠡᑇᖕֆڤڕՀΚ
)]
k ( x min[
)]
k ( x max[
) k ( x )]
k ( x ) max[
k (
x ( )
i )
( i
) ( i )
(
* i
i 0 0
0 0
−
= − ...(4)
)έ*ఖҬኵᐃ౩!
ᅝေᦸࢨ։࣫ᑇᖕᇷறਢאყ൷२ؾᑑଖΰOBαყࠋழΔঞආشψඨؾᑇ ᖕωֱڤࠐၞ۩ᑇᖕᇷற᠏ངΔࠡխmax[xi(0)( )]k ।قਬԫᑇ٨ࢨਢءઔߒඒ ஃေᦸᑓীհਬԫᄷঞΰီᏁޣۖࡳαऱ່ՕଖΔۖmin[xi(0)( )]k ।قᇠᑇ٨ࢨਢ ءઔߒඒஃေᦸᑓীհਬԫᄷঞΖࠡᑇᖕֆڤڕՀΚ
{ }
(0)
*
(0) (0)
( ) ( ) 1
max max[ ( )] , min[ ( )]
i i
i i
x k OB
x k
x k OB OB x k
= − −
− − ...(5)
ພᔃፖܦዧႂΰ1998α᧭ᢞנڼጟᑇᖕছֱऄ٤ຝຟਢᒵࢤऱΰڂڼ
؈ట࿓৫່܅αΔຟ౨ނ务ࠩؾᑑ່Օଖ᠏ངࠩ 1Δۖނ၏ᠦؾᑑଖ່ऱଖ᠏
ངࠩ 0Δ࣍ਢ᠏ངመऱᑇᖕᇷறױאࠠڶઌᅝړऱԫીࢤΔຍՈਢءઔߒආشڼ ԫֱऄᑇᖕᇷறΔ᠏ང৵ऱᑇᖕᇷறլ܀ױאװۯၞ۩ֺለΔՈٵழࠠڶ ড়ᨠࢤ֗ڶயࢤΖ
ʠăWJLPS ٲ!
VIKORΰ Serbian: VlseKriterijumska Optimizacija I Kompromisno Resenje, means: Multicriteria Optimization and Compromise Solutionαऄਢط Opricovic
ΰ1998, 2002αᖂृࢬ༼נΔਢ᥆࣍ڍᄷঞެΰMulticriteria Decision Making, MCDMαխ່ࠋ֏ֱऄΰCompromise ProgrammingαհԫΔءઔߒႛࠌش VIKOR ऄխհඈݧֱऄΖ
VIKOR ඈݧऄհഗءᨠ࢚ԯڇ࣍٣ࡳუᇞΰ່ࠋᇞΔPositive-ideal
solutionαፖუᇞΰ່ᇞΔNegative-ideal solutionαΔࢬᘯუᇞਢਐ࠹ေᦸ
ඒஃڇٺေᦸᄷঞխ౨ࠩհ່ࠋଖΰ100 ։αΙۖუᇞঞਢ࠹ေᦸඒஃڇٺ
ေᦸᄷঞխ౨ࠩհ່ଖΰ0 ։αΔᅝڇެࡳ࠹ေᦸඒஃ່ࠋழΔࠡᨠ࢚ᅝڶ
࠹ေᦸඒஃڇٺေᦸᄷঞՂፖუᇞհ၏ᠦ᜔ፖ່२Δۖፖუᇞհ၏ᠦ᜔ፖ
່Δঞᇠ࠹ေᦸඒஃ່ࠋΔᅝྥΔૉലٺ࠹ေᦸඒஃհ᜔၏ᠦၞ۩ඈݧΔܛ ױګԫඈݧֱऄΖVIKOR ऄհࠌشࠠڶՀ૪༓ႈޡᨏΔࠀ։૪ڕՀΚ(ԫ)ૠጩ إ֏ေ۷ଖΙ(Բ)ެࡳუᇞፖუᇞΙ(Կ)၏ᠦ֗ጵٽਐᑑૠጩΖ
)Ι*ॎᆗғೣϽຟե!
إ֏ေ۷ଖऱΔࠡխ Xijร i ֱூڇร j ေ۷૿հࡨေ۷ଖΔٻၦ إ֏ૠጩֆڤڕՀڤΖ
/ 2 1
1, 2, ..., 1, 2, ..., m ,
X Xij
ij ij i
f = ∑ i m j n
= = < = ... (6)
)Π*ؚۡ౩ད၌ᇄ॒౩ད၌!
ڼޡᨏএެࡳٺ࠹ေᦸඒஃڇٺေᦸᄷঞհࢬ౨ࠩऱ່ࠋ່֗հᜎய ଖΔאঁ܂၏ᠦૠጩհഗ៕ΔࠡૠጩֆڤڕՀΚ
*
j i ij
f =Max f , i=1, 2, ..., m... (7)
j i ij
f− =Min f , i=1, 2, ..., m ... (8)
ࠡխΔf*j j ေᦸᄷঞհუᇞΔร fj−ร j ေᦸᄷঞհუᇞΔૉലࢬ ڶऱ fj*ٽࠓڇԫದګٺ࠹ေᦸඒஃڇေᦸᄷঞհٺႈᜎயଖΔܛԫ່ࠋิ
ٽΔრܛڇՕᖂڣ৫ඒஃေᦸ࠹ေᦸඒᦸΔࠡٺႈ।່݁ࠋऱ।ΰ։αΔ ٵΔfj−ٽࠓڇԫದΔܛԫ່ิٽΔ।قᇠඒஃڇٺေᦸᄷঞհ։ΰᜎய ଖα່݁܅Ζ
)έ*ຽᚔЅᆣӫࡾॎᆗ!
ڼ㩜ᨏܛشࠐૠጩנٺေᦸඒஃڇٺေᦸᄷঞհᜎயଖઌኙ࣍უᇞհ၏
ᠦΔ٦ലࠡף᜔Δא࠷ԫጵٽਐᑑΔࠡૠጩֆڤڕՀΚ
( ) ( )
n * *
i i j ij j j
j
S =∑w f − f / f − f− ...(9)
(
f f) (
/ f f)
][w Max
R i *j ij *j j
i = j − − − ... (10)
ࠡխΔSiร i ֱூΰร i ࠹ေᦸඒஃαუᇞ၏ᠦΰ່ࠋิٽαհ၏ᠦֺଖΔ Riร i ֱூΰร i ࠹ေᦸඒஃαუᇞ၏ᠦΰ່ิٽαհ၏ᠦֺଖΖਚൕᖞ
᧯ࠐΔSiএ।قร i ଡ࠹ေᦸඒஃፖ່ࠋิٽऱ၏ᠦֺଖΔૉലڼଖၞ۩ඈݧΔ ܛױࠩ।ᚌฆ࿓৫ऱඈݧΙٵΔRiܛ࠹ေᦸඒஃፖ່ิٽऱ၏ᠦֺଖΔ
ૉലڼଖၞ۩ඈݧΔܛױࠩ।լߜ࿓৫ऱඈݧΖࠡڻΔ٦אՀ૪ֆڤૠጩࠡ
ጵٽਐᑑΚ
* *
i i
i * *
S S R R
I v[ ] (1 v)[ ]
S− S R− R
− −
= + −
− − ... (11)
ࠡխΔS* = MinSi, S- = MaxSi, R*= MinRi, R- = MaxR*Δۖ ν ঞԫᦞૹᑇΔ ط࣍[(Si-S*)/(S--S*)]।قร i ࠹ေᦸඒஃ၏უᇞհ၏ᠦֺଖΔ।قՕڍᑇԳ݁ᢥ ٵร i ֱூհֺଖΰMajority ruleαΔۖ[(Ri-R*)/(R--R*)]ঞ।قร i ֱூ၏უʳ ʳ ᇞհ၏ᠦֺଖΔࠡࢬڶԳ।ق֘ኙร i ࠹ေᦸඒஃհֺࠏΔڂڼΔᅝ ν ᑇଖყ Օழΰ>0.5αΔ।ق Ii ࢬࠩऱਐᑑലყೣٻڍᑇެΰMajority ruleαΔ֘հΔঞਢ ለೣٻ່՛֘ኙᜢհެࡳΔڂڼΔެृױီᏁᓳᖞڼᑇհՕ՛Δຏൄᇠ
ᑇ݁ࡳ 0.5 ለڍΖ
ءઔߒհࢬא৬ᤜᄅێਬഏمՕᖂലࠐڇေᦸඒஃழආش VIKOR ऄհ
ڂΔਢᅝิ៣ၞ۩ψඒஃေᦸωழΔՕᖂิ៣խհޢۯඒஃڇٺႈေᦸᄷঞՂհ
।݁լٵΔࠏڕᅝ A ඒஃࠡٺႈေᄷᦸᄷঞ।݁ࠋΰ14 ႈ݁ 90 ։αΔ܀ਢ ڇਬႈေᦸᄷঞՂΰڕഏ؆ཚע֮ີ࿇।α।ॺൄΰႛ 1 ႈ 10 ։αΔࠡඒ ஃေᦸ᜔ᜎயଖױ౨ਢ 1270 ։Δۖ B ඒஃࠡٺႈ।݁ڇֽᄷհՂΰ15 ႈ݁
80։αΔ᜔ࠡᜎயଖױ౨ਢ 1200 ։ΖڕਢΔאՕᖂิ៣ऱᨠរࠐΔለݦඨ B ඒ
ஃऱەᜎᚌ࣍ A ඒஃΔ܀אՂ૪հ១ףᦞऄࢬհ᜔ᜎயଖΔലᄎᎄᖄࠡ࣠Δ ࠌ A ඒஃհᜎயᚌ࣍ B ඒஃΰ1270 > 1200αΔ܀ຍࠀॺՕᖂጥၸᐋࢬუᛧ
ऱ࣠ΔڂڼΔءઔߒࢬ৬ᤜհ VIKOR ඈݧऄΔࠡ Si।قࢬڶ࠹ေᦸඒஃ່ࠋ
ิٽհ᜔၏ᠦֺଖΔ᥆࣍ڍᑇެհ࣠ΔױലࠡඈݧΔ܂รԫەᑇᖕΔۖ Ri ঞ।قࢬڶ࠹ေᦸඒஃ၏ᠦ່।հ᜔၏ᠦֺଖΔ᥆່՛֘ኙᜢհਐᑇΔࠡ
ඈݧױԫەࠉᖕΔ່৵ࡳ ν 0.5ΔܛױٵழەၦڍᑇެΔٍױࣹრࠩլ ױڶਬႈေᦸᄷঞհᜎயመ܅հൣݮΔڼរܛፖՕᖂᜤࢵਬߓࢬڇਬࠄઝؾՂ
ޣլױ܅࣍ࡳ։ᑇհრᆠઌ२Ζ
དྷă̂ጯିरෞᝥቑּనࢍᑕϡ
ءઔߒଈ٣ࠉᖕઔߒؾऱࠐᒔمઔߒऱֱٻፖૹ֨Δ٦ەሎشՂᆏઔߒֱ
ऄΔ܂ءઔߒՕᖂඒஃေᦸᒤࠏૠᚨشհەΖଈ٣ᎅࣔءઔߒࢬ֧شऱψඒ ஃေᦸઔߒᑓীω֗ᙇ࠷ءઔߒψඒஃေᦸᄷঞऱᦞૹωΔ٦ٽՂᆏઔߒֱऄऱ
ࢤΔၞ۩ءઔߒऱᒤࠏૠΖ
ʙăࣱඟᜦࠂՀᇁܮ!
ءઔߒەޕࡲᤌΕຫᮾΕຫةႉፖᇄݕګΰ2003αᖂृܓشڍေᄷެࡳ
ऄ൶ಘψՕᖂඒஃᜎயေᦸᑓী৬م֗։࣫ωΔۖࢬ৬مऱඒஃေᦸᑓীΖᇠઔߒ
ಾኙᄅێਬഏمՕᖂࢬڶߓࢬၞ۩ኔᢞ։࣫ᓳΔڇߓࢬٽԫऱඒᖂۯٺ࿇נ 15ٝം࠴Δઔߒࢬऱඒᖂۯ࿇נ 6 ٝം࠴Δ٥ૠ࿇נ 402 ٝം࠴Δڃگ 290 ٝ
ം࠴Δࠀಾኙڃऱം࠴ၞ۩ԫીࢤ։࣫Δᆖᖞڶயം࠴٥ૠڶ 255 ٝΔءઔ ߒ֧شᇠኔᢞ։࣫ࢬऱᦞૹ܂ءઔߒᒤࠏᚨش֗ඒஃေᦸᄷঞऱᦞૹΖᇠඒ ஃေᦸᑓীΔᎁಾኙඒஃေᦸ։࣫ழؘႊەၦԿଡዌ૿֗ 15 ႈေᦸᄷঞΔթߩ אڍֱ૿֗ڶயݙګඒஃေᦸΖࠡխڇေᦸዌ૿ץਔΚ(ԫ)ඒᖂګ࣠ዌ૿Ι(Բ) ઔߒګ࣠ዌ૿Ι(Կ)ࣚ೭ګ࣠ዌ૿Δۖޢԫေᦸዌ૿ຟץਔ 5 ႈᣂᜤࢤᄷঞΔᇡ ڕቹ 1Ζ
ၗٰྍǺےᝬǵഋ᨞൛ǵഋ҉ǵဤֵԋȐ2003ȑǶεᏢ௲ৣᕮਏຑ᠘ኳࠠࡌҥ ϷϩаཥԮࢌ୯ҥεᏢࣁٯǶዺύǶ
1! ˃ደࣱᑼझඟᜦࠂՀᇁܮ
ʠăࣱඟᜦລ܌ڟᜌࡧ!
ᇠഏمՕᖂ٥ڶሽᖲᇷಛᖂೃΕՠᖂೃΕᖂೃΕጥᖂೃΕԳ֮षᄎᖂೃΔ א֗٥ٵઝፖඒᖂխ֨քՕඒᖂۯΔءઔߒಾኙޢԫଡᖂೃ࿇נം࠴Δڃگ
࣠ڕ। 2 ࢬقΔࠀ֧شጥᖂೃؓ݁ᦞૹΔࠐ܂ءઔߒඒஃᜎயေᦸᄷঞհᦞ ૹΖጥᖂೃေᦸᄷঞᦞૹਢطᇠೃऱ 48 ۯඒஃΔኙቹ 1 ऱ 15 ေᦸᄷঞᦞૹऱ
ऄ֗ઌኙૹီ৫հؓ݁ଖΔڕ। 3Ζ
ඒᖂᔆ˂ᖂسေរʳ ਐᖄᖂس֗յ೯ʳ ᓰ࿓໌ᄅʳ
ඒᖂᄷໂЯඒޗᒳᐷʳ ᓰ࿓ቤ֗ڜඈʳ
ᖂீ۩ਙՠ܂
ᖂீഗ८հᣠႥ
ٚᖂسᖄஃ֗᎖ᖄ
ਐᖄᖂسףீ؆ᤁ
ፖֆ٥ਙ֗ֆ墿ቸ᧯
ഏ؆ཚע֮ີ࿇।ΰSCI,SSCI,EIα ഏփཚע֮ີ࿇।ΰᚌߜཚעα റܓᛧЯ໌ᄅ܂
ૠЯറூઔߒᛧ
ઔߒᑻᚐᛧ
ࣚ೭ګ࣠ʳ ઔߒګ࣠ʳ ඒᖂګ࣠ʳ
ࠂՀάڟ! ඟᜦ်! ඟᜦລ܌!
৬مՕᖂඒஃᜎயေᦸ ΰࢨေၦΕေᐉαᑓী
ے2! Ϩደੰ֢ϱНࡎے
ደᘸѿ വ͎ੰ֢Ğϋğ ϱНੰ֢Ğϋğ Фझੰ֢Ğϋğ Фझੰ֢͛ϒ̨ս ሽᖲᇷಛᖂೃ 96 65 57 22.35%
ՠᖂೃ 60 47 41 16.08%
ᖂೃ 84 52 47 18.43%
ጥᖂೃ 81 57 48 18.82%
Գ֮षᄎᖂೃ 51 44 39 15.29%
٥ٵઝ֗ඒᖂխ֨ 30 25 23 9.02%
᜔ૠЯֺࠏ 402 290 255 100.00%
ے3! Ϩደ̆ᐖࣱᑼझඟᜦລ܌˞ᜌࡧ
ደЙَ ࠂՀЙَ وਜ਼Йَ
ѿƝ ᜌࡧĞ
ӕğ Ɲά
ደܢቴჄደΡඟᔈ ደΡݾዲ̅ˣ ു̅ᘸѿ ደລరჄԅሡᆥ ു࿒̅Њ ʹೈ̜͐ణവے ˱ೈ̜͐ణവے ટҁᑕુჄѰܢ ࡎഫჄટरࠂՀᑕુ ࠂՀᇩᑕુ ደमїއˎѰ ደमઅۜ˞ᙎณ ψᕛደΡዲࣱ̅ᄄዲ ݾዲደΡमʹᙯᓉ ˴ϓއൊ̅˴উ͑
ྫጠཥ ਉደ
0.066 (5)
0.077 (4)
0.061 (8)
0.063 (6)
0.057 (9)
0.203 (1)
0.053 (10)
0.078 (3)
0.063 (6)
0.096 (2)
0.042 (12)
0.033 (14)
0.049 (11)
0.037 (13)
0.023 (15) ˎደ 0.084
(4) 0.082
(5) 0.057
(9) 0.065
(7) 0.065
(7) 0.166
(1) 0.054
(10) 0.090
(3) 0.073
(6) 0.093
(2) 0.037
(12) 0.031
(14) 0.045
(11) 0.032
(13) 0.028
(15) ୩ደ 0.091
(2) 0.053
(9) 0.069
(6) 0.069
(6) 0.066
(8) 0.175
(1) 0.048
(10) 0.072
(5) 0.077
(4) 0.086
(3) 0.040
(12) 0.033
(15) 0.044
(11) 0.040
(12) 0.037
(14) ႓ ୩
ደ 0.088
(2) 0.077
(5) 0.062
(8) 0.060
(9) 0.064
(7) 0.165
(1) 0.083
(3) 0.078
(4) 0.059
(10) 0.067
(6) 0.041
(12) 0.034
(14) 0.051
(11) 0.040
(13) 0.030
(15) ʡ̜ڥ
ደ
0.042 (10)
0.067 (6)
0.045 (9)
0.042 (10)
0.039 (13)
0.179 (1)
0.078 (4)
0.126 (2)
0.077 (5)
0.088 (3)
0.041 (12)
0.056 (7)
0.037 (14)
0.035 (15)
0.049 (8) ϓϣࠋ ̅ደ
˛ ̖ 0.118
(1) 0.073
(6) 0.067
(7) 0.086
(4) 0.097
(3) 0.107
(2) 0.044
(12) 0.077
(5) 0.051
(10) 0.065
(8) 0.054
(9) 0.034
(15) 0.039
(13) 0.050
(11) 0.037
(14) ᒂӕ (4) (5) (8) (8) (10) (1) (7) (2) (6) (3) (12) (13) (11) (13) (15) ຏǺ܌Ԗϩीᆉۓᇤৡॶλܭ 0.002
ʭăሒս௩ࡎჳق!
ڶ n ۯඒஃၞ۩ඒஃေᦸࠀᆖطءઔߒԿՕዌ૿խऱ 15 ႈေᄷঞᦞૹΰאٺ ᖂೃհؓ݁ᦞૹαΔٽޢۯඒஃڇ 15 ႈေᄷঞᦞૹࢬᛧհᜎயଖΰطۊ ᣂᑇᖕছᑇΫඨՕᑇᖕֆڤ(3)Δޣٺ࠹ေᦸඒஃհေᦸᄷঞᜎயଖαΔ ڕ। 4 ࢬقΖ
ے4! ࣱඟᜦሒսᇁܮ௩ࡎ
ႈ ؾ Я ေ ᦸ ᄷঞ
ඒᖂᔆፖᖂسေរ ᖂسਐᖄ֗յ೯ ᓰ࿓໌ᄅ֗ᣊܑ ඒᖂᄷໂፖඒޗᒳᐷ ᓰ࿓ቤ֗ڜඈ ഏ؆ཚע֮ີ࿇। ഏփཚע֮ີ࿇। റܓᛧፖ໌ᄅ܂ ૠፖറூઔߒᛧ ઔߒᑻᚐᛧ ᖂீ۩ਙՠ܂ ᖂீഗ८հᣠႥ ٚᖂسᖄஃ֗᎖ᖄ ਐᖄᖂسீ؆ᤁ ֆ٥ਙ֗ֆ墿ף
ٺ ᖂ ೃ
ؓ ݁ ᦞ ૹ w1 w2 w3 w4 w5 w6 w7 w8 w9 w10 w11 w12 w13 w14 w15
1 f11 f12 f13 f14 f15 f16 f17 f18 f19 f110 f111 f112 f113 f114 f115
2 f21 f22 f23 f24 f25 f26 f27 f28 f29 f210 f211 f212 f213 f214 f215
… … …
… … … ᅝ ཚ ࠹
ေ ᦸ ඒ ஃ Գ ᑇ ᒳ ᇆ ֗
ᜎயଖ n fn1 fn2 fn3 fn4 fn5 fn6 fn7 fn8 fn9 fn10 fn11 fn12 fn13 fn14 fn15
უ ᇞ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ fjϠ
უ ᇞ fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
fj—
࠹ေᦸඒஃ უᇞ၏ᠦRi უᇞ၏ᠦSi ඒᖂᔆፖᖂسေរ ᖂسਐᖄ֗յ೯ ᓰ࿓໌ᄅ֗ᣊܑ ඒᖂᄷໂፖඒޗᒳᐷ ᓰ࿓ቤ֗ڜඈ ഏ؆ཚע֮ີ࿇। ഏփཚע֮ີ࿇। റܓᛧፖ໌ᄅ܂ ૠፖറூઔߒᛧ ઔߒᑻᚐᛧ ᖂீ۩ਙՠ܂ ᖂீഗ८հᣠႥ ٚᖂسᖄஃ֗᎖ᖄ ਐᖄᖂسீ؆ᤁ ֆ٥ਙ֗ֆ墿ף
ร
ۯ1 R1j S1j S11 S12 S13 S14 S15 S16 S17 S18 S19 S110 S111 S112 S113 S114 S115
ร
ۯ2 R2j S2j S21 S22 S23 S24 S25 S26 S27 S28 S29 S210 S211 S212 S213 S214 S215
… … … … … … … … … … … … … … … … … …
… … … … … … … … … … … … … … … … … …
ร
ۯn Rnj Snj Sn1 Sn2 Sn3 Sn4 Sn5 Sn6 Sn7 Sn8 Sn9 Sn10 Sn11 Sn12 Sn13 Sn14 Sn15
طֆڤ(6)Ε(7)Ε(8)נ। 4 խࢬհٺ࠹ေᦸඒஃუᇞ֗უᇞΔၞۖ
طֆڤ(9)Ε(10)ޣנٺေᦸඒஃڇٺေᦸᄷঞհᜎயଖઌኙ࣍უᇞ၏ᠦΔڇࠉ ֆڤ(11)ૠጩޢۯඒஃ᜔ᜎயଖΔࠀၞ۩ඈݧေᦸנᚌߜඒஃࢨฤٽ֒ᇷհ ඒஃΰڕ। 5αΖࠡխᅝ ν ᑇଖყՕழΰ> 0.5αΔ।ق Ii ࢬࠩऱਐᑑലყೣٻ ڍᑇެΰMajority ruleαΔ֘հΔঞਢለೣٻ່՛֘ኙᜢհެࡳΔڂڼΔެृ
ױီᏁᓳᖞڼᑇհՕ՛Δຏൄᇠᑇ݁ࡳ 0.5Ζ ے5! nѝ֧ඟᜦࣱᒂᑼझࢄӕے
֧ඟᜦࣱƝᒂᑼझ
ࢄ̅ӕƝvࢄ 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
1ѝ֧ඟࣱ I1 I1 I1 I1 I1 I1 I1 I1
2ѝ֧ඟࣱ I2 I2 I2 I2 I2 I2 I2 I2
… … … … … … …
… … … … … … …
nѝ֧ඟࣱ In In In In In In In In
Ёă၁ᙋ̶ژ̈́ኢ
ءᆏലאጥᖂೃඒஃ֒ေᦸᒤࠏΔࠀאጥᖂೃᓳઔߒऱؓ݁ᦞૹ
ഗᄷΔࠀԵ 5 ۯඒஃ֒ٺႈေᦸᄷঞࢬհᜎயଖΔࠐၞ۩ᒤࠏኔᎾᚨش ᎅࣔΖଈ٣ආ࠷ေᦸᄷঞᦞૹΰڕ। 3αΔ٦ޣ࠷ޢۯ࠹ေᦸඒஃᜎயଖΔࠀၞ۩
ޢۯඒஃհუᇞ֗უᇞऱૠጩΔࠉᖕছ૿ऱუᇞ֗უᇞࠐޣ࠷ඒஃ հუᇞ၏ᠦ֗უᇞ၏ᠦΔ່৵ጵᖞ֗ඈݧ࠹ေᦸ֒ඒஃ᜔ᜎயଖΖ
ʙăඟᜦລ܌ᜌࡧ!
ءઔߒආشጥᖂೃ 5 ۯඒஃ֒ᒤࠏΔਚא। 6 խጥᖂೃऱ 15 ႈေᦸ ᄷঞऱᦞૹΔ܂ૠጩޢۯေᦸඒஃᜎயհഗ៕Ζڇ 15 ႈေᦸᄷঞऱᦞૹࠡխΔ אഏ؆ཚע֮ີ࿇।ऱ 0.165 ່Εࠡڻඒᖂᔆፖᖂسေរऱ 0.088 ፖഏփ ཚע֮ີ࿇। 0.083Δ່܅ֆ٥ਙ֗ֆ墿ף 0.030Ζ
ے6! ႓୩ደ15ඟᜦລ܌үᜌࡧ
ደЙَ! ࠂՀЙَ! وਜ਼Йَ!
άƝ ඟᜦລ
܌!
ደܢቴჄደΡඟᔈ! ደΡݾዲ̅ˣ! ു̅ᘸѿ! ደລరჄԅሡᆥ! ു࿒̅Њ! ʹೈ̜͐ణവے! ˱ೈ̜͐ణവے! ટҁᑕુჄѰܢ! ࡎഫჄટरࠂՀᑕુ! ࠂՀᇩᑕુ! ደमїއˎѰ! ደमઅۜ˞ᙎณ! ψᕛደΡዲࣱ̅ᄄዲ! ݾዲደΡमʹᙯᓉ! ˴ϓއൊ̅˴উ͑!
ጥ
ᖂೃ
0.088 (2)
0.077 (5)
0.062 (8)
0.060 (9)
0.064 (7)
0.165 (1)
0.083 (3)
0.078 (4)
0.059 (10)
0.067 (6)
0.041 (12)
0.034 (14)
0.051 (11)
0.040 (13)
0.030 (15)
ʠă֧ඟᜦࣱᑼझࢄ!
ءઔߒᒤࠏڇՕᖂڣ৫ψඒஃ֒ω܂ᄐ࠹ေᦸඒஃհᜎயଖΔආشᑓᚵඒ ஃ֒ေᦸᚨشᇷறΔᆖطۊᣂᜤᑇᖕছ৵Ζءઔߒ 15 ႈေᦸᄷঞᑇᖕᇷற
ਢאყՕყࠋΔਚආشψඨՕᑇᖕωֱڤࠐၞ۩ᑇᖕᇷற᠏ངΔࠡ 5 ۯඒ ஃٺႈေᦸᄷঞࢬհᜎயଖΰଊՂ 100αΔᇡڕ। 7Ζ
ے7! ˤѝ֧ඟᜦࣱ˞ᑼझࢄ
ደЙَ ࠂՀЙَ وਜ਼Йَ
άƝ ඟᜦລ
܌
ደܢቴჄደΡඟᔈ ደΡݾዲ̅ˣ ു̅ᘸѿ ደລరჄԅሡᆥ ു࿒̅Њ ʹೈ̜͐ణവے ˱ೈ̜͐ణവے ટҁᑕુჄѰܢ ࡎഫჄટरࠂՀᑕુ ࠂՀᇩᑕુ ደमїއˎѰ ደमઅۜ˞ᙎณ ψᕛደΡዲࣱ̅ᄄዲ ݾዲደΡमʹᙯᓉ ˴ϓއൊ̅˴উ͑
1 90 90 90 90 90 50 90 90 90 80 90 90 90 90 90
2 80 80 86 84 80 60 88 80 70 60 80 82 50 80 83
3 88 85 85 85 85 70 85 85 85 85 80 85 80 80 80
4 85 85 87 85 85 80 85 85 85 86 88 85 89 89 80
໋ೈ֧ඟᜦࣱᑼझࢄ
5 70 70 70 70 70 90 80 80 80 80 80 80 80 80 85
ᇷறࠐᄭΚᑓᚵඒஃ֒ေᦸᇷற
ʭă୩๑ཌ̅ࡒ୩๑˞ԑ֥!
ءޡᨏএڇެࡳٺ࠹ေᦸඒஃΔڇٺေᦸᄷঞհࢬ౨ࠩऱ່ࠋ່֗հᜎ யଖΔאঁ܂၏ᠦૠጩհഗ៕Δնۯ࠹ေᦸඒஃڇ 15 ႈᄷঞᜎயଖհუᇞ֗
უᇞΔࠉᖕ। 7 նۯඒஃᜎயଖΔױ। 8 հ 15 ႈᄷঞٺଡუᇞ֗უ ᇞΖ
ے8! ˤѝ֧ඟᜦࣱϵ15ລ܌ᑼझࢄ˞୩๑ཌ̅ࡒ୩๑ཌࡎے
ደЙَ ࠂՀЙَ وਜ਼Йَ
άƝඟᜦລ܌ ደܢቴჄደΡඟᔈ ደΡݾዲ̅ˣ ു̅ᘸѿ ደລరჄԅሡᆥ ു࿒̅Њ ʹೈ̜͐ణവے ˱ೈ̜͐ణവے ટҁᑕુჄѰܢ ࡎഫჄટरࠂՀᑕુ ࠂՀᇩᑕુ ደमїއˎѰ ደमઅۜ˞ᙎณ ψᕛደΡዲࣱ̅ᄄዲ ݾዲደΡमʹᙯᓉ ˴ϓއൊ̅˴উ͑
უᇞ 90 90 90 90 90 90 90 90 90 86 90 90 90 90 90
უᇞ 70 70 70 70 70 50 80 80 70 60 80 80 50 80 80
Ͳăࣱ˞୩๑ཌලᖔ̅ලࡒ୩๑ཌලᖔԑ֥!
ءޡᨏܛشࠐૠጩנٺေᦸඒஃΔڇٺေᦸᄷঞհᜎயଖઌኙ࣍უᇞհ၏
ᠦΔ٦ലࠡף᜔Δא࠷ޢۯ࠹ေᦸඒஃհጵٽਐᑑუᇞ၏ᠦΰSiα֗უ ᇞ၏ᠦΰRiαΔڕ। 9Ζ
ˤằࣱᒂᑼझࢄࡎ႗̅ӕ!
ط ν ԫᦞૹᑇΔءઔߒቫᇢല ν 0.1 ۟ 0.8Δၞ۩Զᣊ ν ᑇଖඒஃ
᜔ᜎயଖૠጩ֗ඈݧΔ࣠ڕ। 10Ζࠉᖕ VIKOR ऄऱ֗᧭ጩࡳΔᅝ ν ᑇଖყՕழΰ> 0.5αΔ।ق IiࢬࠩऱਐᑑലყೣٻڍᑇެΰMajority ruleαΔ֘հΔ ঞਢለೣٻ່՛֘ኙᜢհެࡳΔڂڼΔءઔߒ ν ᑇ 0.5 ࢬඒஃ᜔ᜎயଖ
ၞ۩ֺለ֗ඈݧΖਚࠉᖕ։࣫ૠጩ࣠ร 4 ۯඒஃΕร 3 ۯඒஃ֗ร 1 ۯඒஃ᜔
ᜎயଖՕ࣍ 0.5Δਚᚨฤٽ֒ᇷΖ
ے9! ˤѝ֧ඟᜦࣱϵ15ລ܌ᑼझࢄ˞୩๑ཌලᖔ̅ࡒ୩๑ཌ ලᖔ
άƝඟᜦ
ລ܌ ደЙَ ࠂՀЙَ وਜ਼Йَ
֧ඟᜦࣱ ࡒ୩๑ཌලᖔRi ୩๑ཌලᖔSi ደܢቴჄደΡඟᔈ ደΡݾዲ̅ˣ ു̅ᘸѿ ደລరჄԅሡᆥ ു࿒̅Њ ʹೈ̜͐ణവے ˱ೈ̜͐ణവے ટҁᑕુჄѰܢ ࡎഫჄટरࠂՀᑕુ ࠂՀᇩᑕુ ደमїއˎѰ ደमઅۜ˞ᙎณ ψᕛደΡዲࣱ̅ᄄዲ ݾዲደΡमʹᙯᓉ ˴ϓއൊ̅˴উ͑
ร
ۯ1 0.165 0.180 0.000 0.000 0.000 0.000 0.000 0.165 0.000 0.000 0.000 0.015 0.000 0.000 0.000 0.000 0.000
ร
ۯ2 0.124 0.669 0.044 0.039 0.012 0.018 0.032 0.124 0.017 0.078 0.059 0.067 0.041 0.027 0.051 0.040 0.021
ร
ۯ3 0.083 0.396 0.009 0.019 0.016 0.015 0.016 0.083 0.042 0.039 0.015 0.003 0.041 0.017 0.013 0.040 0.030
ร
ۯ4 0.042 0.279 0.022 0.019 0.009 0.015 0.016 0.041 0.042 0.039 0.015 0.000 0.008 0.017 0.001 0.004 0.030
ร
ۯ5 0.088 0.700 0.088 0.077 0.062 0.060 0.064 0.000 0.083 0.078 0.030 0.015 0.041 0.034 0.013 0.040 0.015
