遺伝的アルゴリズムによる漁労利益最大漁船の主要 目の検討

目の検討

著者 衛 ?, 永松 哲郎

雑誌名 鹿児島大学水産学部紀要=Memoirs of Faculty of Fisheries Kagoshima University

巻 57

ページ 1‑10

別言語のタイトル Study on Principal Particulars of a Fishing Vessel with the Maximum Fishery Profit by Genetic Algorithms

URL http://hdl.handle.net/10232/8078

Mem. Fac. Fish. Kagoshima Univ., Vol. 57, pp. 1~10 (2008)

2 ৅ ঱ ോ ఱ ڠ କ ॲ ڠ ໐ ݽ ު ࢥ ڠ ໦ ࿤(Fisheries Engineering, Faculty of Fisheries, Kagoshima University, 61-31 Shimoarata 5, Kagoshima, 9:1-1167 Japan) ȁ

Corresponding author, E-mail: nagamatu@fi sh.kagoshima-u.ac.jp

֒ഥഎͺσΌςΒθͥ͢ͅݽႻ၌ףडఱݽ஑͈৽ါ࿒͈࠿൦

߃ාȄݽު঩࡙͈ࡘઁȄݽث͈೩ྸȄକॲ໤࿶වၾ

͈௩ఱȄݽ஑ݽުਲম৪͈ࣞႢا͂ࢃࠑ৪ະ௷Ȅయ஑࠺

௮ၾ͈ࠣࡘȄݽ஑ݽުࠐאఘ͈ञྩ಼ًȄࢵͅීၳثڒ

͈ࣞ൯̈́̓Ȅ඾ུ͈ݽ஑ݽުͬ৾ͤے̩۪ޏ͉ࡕ̱̯ͬ

௩̱̞̀ͥȃ̭͈̠̈́͢ેޙ͈ئ́Ȅ੿ြ͈඾ུ͈ݽ஑

ݽުܿ੅̧͈̜͓ͥউͬࡉ੄̳দ͙̦࣐̞ͩͦ̀ͥ^2ȫ3ȫȃ

ࣽࢃȄݽ஑ݽު̦୆̧ॼ̹͉ͥ͛ͅഐ୨̥̾ࡕڒ̈́କॲ

঩࡙ۯၑ͈ئ́Ȅनॳ଻͈̞ࣞݽ஑͈ٳอ̦ݥ͛ͣͦ̀

̞ͥ^4ȫȃ̷͈̹͉͛ͅȄݽ஑͈જ΀Υ͞જႁاȄ೩΋Α ΠاȄݽڕ໤͈຦ৗ͞஛ഽ༗঵͈ࣞഽاȄհ஠଻͞ݳਯ

଻͈̞ࣞݽ஑͞ݽႻ௡౾͈ٳอȄී๯࢜ષ͈̈́̓ڟ૧എ

̈́ܿ੅ٳอ̦ຈါ̜̠́ͧȃ

̭͂ͧ́Ȅड߃ཤ؎ݽ஑͂඾ུ͈ݽ஑ͬ๤͓ͥ͂Ȅ஑

߿̦ఱ̧̩֑̠̭̦͂ঐഊ̯ͦ̀Ȅ඾ུ߿ݽ஑͈ࡉೄ̱

̧͈̥̫̞̽̈́̽̀ͥͅ^5ȫ6ȫȃ໹଼25ා9࠮ͅ൲ႁ஑͈

଻ෝܖ੔͈ࡔ௱෱গȄঐ೰ݽު͈ݺخ̤̫ͥͅݽ஑͈Π ϋତٴ௄ߊ໦͈ࡉೄ̱൝̦࣐ͩͦ̀Ḙ͉֑̏ͦ́͂̽͘

̹૧̱̞ݽ஑͈஑߿ٳอ͈ܥ׋̦ࣞͤ͘Ȅनॳ଻͈̞ࣞ

஑߿̦ݥ̠̹͛ͣͦͥ̈́̽͢ͅȃ؎ਗ͈ݽ஑͈̠̈́͢ࢩ

̞ࢿโ࿂ୟ͞ܥ٫ا͈ଔૺͤ͢ͅજ΀ΥσΆȜȆજ૽Ȇ જႁاȄ໼͍ͅैު۪ޏ͈٨஝Ȇ٨ၻ̦خෝ̥͂̈́ͥ͜

̱̞ͦ̈́ȃ

̭͈̠͢ͅḘ̥͈̏ͦͣݽ஑͉̭͈ͦ́͘ݽ஑͉͂

֑̹̽૧̱̞஑߿͈੄࡛̦ݥ̦͛ͣͦͥȄݽ஑ݽު͈

࠲஠̈́ͥࠐא࣐̠̹͉͈̠ͬ͛̓̈́͢ͅ஑߿̧̳͓̥͂

দ࣐॒ࢋ̯̞ͦ̀ͥȃ̭͉ͦ́͘஑ఘ೷ࢯ̦ड઀͂̈́ͥ

Abstract

Genetic algorithm GA is widely applied to the non-linear optimum problems in the various technological fi elds. Fishing vessels are faced to serious problems such as low benefi ts, low fi sh prices, lack of young fi shermen and so on. In the present study, the principal particulars of the optimum fi shing vessel which earns the highest benefi t in a year are studied by using the genetic algorithm. At fi rst, two GA methods, bit-string GA and real coded GA, are examined their applicability to the present problem. The results indicate that GA is a useful tool for study on the principal particulars of the fi shing vessel at the initial design stage and there is not much to choose between two GA methods. The optimum ship form is dependent on the ship speed and its block coeffi cient becomes smaller with increase of her speed. A promising solution for the problem of high fuel price is shown to adopt low ship speed and large gross tonnage.

מȁὬȄ^2ȁזઐȁഓ჊^2ɖ

Study on Principal Particulars of a Fishing Vessel with the Maximum Fishery Profi t by Genetic Algorithms

Qi Wei,¹ Tetsuo Nagamatsu^1*

Key words : Bit-string genetic algorithm, Real coded genetic algorithm, Ship resistance, Maximum gross profi t, Roundhaul netter

஑߿Ȅ̜̞͉ͥજ΀Υͬ೏ݞ̱̹஑߿͈ࡄݪ̦৽࣐ͩͅ

̞ͦ̀ͥȃ̷ུ̭́ࡄݪ͉́Ḙ̥͈̏ͦͣݽ஑ݽުࠐא

ͅݥ͛ͣͦͥड͜ਹါ̈́नॳ଻ͅచ̱̀डഐ̈́஑߿ͬࠗ

ْ̳ͥडഐا਀༹̞̾̀ͅ࠿൦̱̹ȃडഐا਀༹͈͌͂

̱̾͂̀Ȅड߃ಕ࿒̯̞͈̦ͦ̀ͥ֒ഥഎͺσΌςΒθ ȪGAȇgenetic algorithmȫ̜́ͥ^7ȫȃ̭͉ͦ୆໤ਅ͈ૺا

ً೾ͬ૯যͥࠁ́ତၑഎ࿚ఴ๊͈֚͒ഐဥͬփ଎̱̀ਬ ౬ͬଲయྀͅಈষ٨ၻ̳ٜͥଢ଼༹̜́ͥȃ༹̭͈༷͉ຈ

̴૯͈डഐٜͬဓ̢̞̠ͥ͂༗બ͉̞̦̈́Ȅࠗॳ͈੝ܢ

ૄ࠯͈୭೰ͅඅ༆̈́Φ;Χ;͉ຈါ̩́̈́Ȅໝॠ̈́࿒എ

۾ତͅచ̱̀͜ယօͅडഐ౵ͅ߃̞ٜͬං̧̭̦ͥ͂́

ͥȄ̞̠͂၌ത̦̜ͥȃ̹͘Ȅఈ͈डഐا਀༹ͅ๤͓̀Ȅ डഐٜͬං͈ͥ́ࠗ͘ॳশۼ͈ౣੀ̦ࡉࣺͦ͘Ȅౝً॑

೾͈ఉအ଻ͤ͢ͅޫਫ਼डഐٜͅۿ̩̞̭ͤ͂͜ͅݷ̬ͣ

̞ͦ̀ͥ^9ȫȃུࡄݪ͉́ȄාۼݽႻ၌ף̦डఱ͂̈́ͥݽ

஑஑߿͈৽ါ࿒̞̾̀ͅȄ֒ഥഎͺσΌςΒθͬဥ̞̀

࠿൦̱̹͈̜́ͥ͜ȃ֒ഥഎͺσΌςΒθ̱͂̀ȄΫΛ ΠΑΠςϋΈGA͂৘ତ౵GA͈3༹͈༷̾ͬဥ̞̹ȃ

֒ഥഎͺσΌςΒθ

֒ഥഎͺσΌςΒθ^8ȫ͉́Ȅఉତ͈ࡢఘ̥ͣ̈́ͥਬ౬

͈ಎ̥ͣ૶͂̈́ͥࡢఘͬໝତ஖఼̱Ȅ૶͈࢐ए̽̀͢ͅ

૶͈අ଻Ȫ௺଻ȫ̧ͬ֨ࠑ̞̺ঊͬ୆̲ͥȃ૶͈஖఼͉Ȅ

࿒എ۾ତ͈౵Ȫഐࣣഽȫ̦ఱ̧̞ࡢఘ̦̞ࣞږၚ́஖఼

̯ͦͥȃ൳̲ࡢఘ̦૶̱͂̀ໝତٝ஖఼̯̭̜ͦͥ͂͜

ͥȃ̷͈ࠫضȂഐࣣഽ͈̞ࣞ௺଻ͬ঵̾ࡢఘ̦ঊః̱͂

̀୆̧ॼͤȂ௩̢̞̩̭̀͂̈́ͥͅȃ

ΫΛΠΑΠςϋΈGÁ͉Ȅ๊͈֚֚̾ͅࡢఘ͉֚̾

͈அ૗ఘ́ນ̯ͦȄஅ૗ఘ͉ఉତ͈֒ഥঊ́ࢹ଼̯ͦ̀

̞̀Ȅڎ֒ഥঊ͉Ȫ1,2ȫ͈3ૺତ́ນ̯ͦͥȃ̳̻̈́ͩȄ அ૗ఘȪࡢఘȫ͉Ȫ1,2ȫ͈֒ഥঊႥȪΫΛΠΑΠςϋΈȫ

́ນ̯ͦͥȃ႕̢͊Ȅ୭ࠗ་ତxͬ6͈ࠥ֒ഥঊ́ນ̳

̳͂ͥ͂Ȅ43ࡢ͈ၗ८എ̈́ତ౵̦x̱͂̀৾ͤංͥํ

ս̞̠̭͂͂̈́ͥͅȃडഐا࿚ఴ̤̫ͥͅໝତ͈୭ࠗ་

ତ͉֒ഥঊ͈ழȪࠥȫͬ໼͓̀ນ࡛̯ͦͥȃ̭͈̠͢ͅ

ΫΛΠΑΠςϋΈGÁ͉་ତ͉ၗ८౵̱͂̀եͩͦͥ

͈́ȄႲ௽۾ତ͈डഐا࿚ఴ͈ાࣣ͉ഐ୨͉͂࡞̢̞̈́ȃ

̭͈̠̈́͢࿚ఴͅచ̱͉̀Ȅ୭ࠗ་ତ͈Ⴒ௽଻̦ږ

༗̯ͦͥ৘ତα·ΠσȪ་ତ̦n͈ાࣣ͉nষࡓ͈α·

Πσȫͬஅ૗ఘͅဥ̞ͥ৘ତ౵֒ഥഎͺσΌςΒθȪ৘

ତ౵GA͂ઠ̳ͥȫ̦೹մ̯̞ͦ̀ͥȃ৘ତ౵GÁ͉

૶̥ͣঊͬ୆଼̳ͥ࢐ए༹͈༷͜ΫΛΠΑΠςϋΈGA Ȫ֒ഥঊႥͬဥ༹̞༷ͥȫ͉͂։̞̈́̽̀ͥȃ৘ତ౵

GA͉୭ࠗ་ତͅ৘ତ౵ͬဥ̞̭ͥ͂́࿒എ۾ତ͈Ⴒ௽

଻ͬࣉၬ̱̹ౝ̦॑خෝ̜́ͥത̥ͣȄΫΛΠΑΠςϋ ΈGA͂๤ڛ̱̀ၻࢡٜ̦̈́ං͈ͣͦͥ͂༭࣬^9ȫ̦̜

̦ͥȄ3͈̾GAͬ๤ڛ̱̹ࡄݪ႕͉ઁ̞̈́ȃུࡄݪ͉́Ȅ

ාۼݽႻ၌ף̦डఱ͂̈́ͥݽ஑஑߿͈डഐ৽ါ࿒̞̾ͅ

̀ඵ͈̾GAȄ̳̻̈́ͩΫΛΠΑΠςϋΈGA͂৘ତ౵

GA̞̾̀ͅ๤ڛ࠿൦̱̹ȃ

་ତ͂ࡢఘ

ΫΛΠΑΠςϋΈGÁ͉་ତx_i͉Ȫ1,2ȫ͈Ⴅ́ນ

̯ͦȄࡢఘyjȪj=2~mȫ͉xiȪi=2~nȫͬ2Ⴅͅ໼͓̀ນ

࡛̯ͦͥȃ̭̭́Ȅn͉་ତ͈ତ́Ȅm͉ࡢఘତ̜́ͥȃ

৘ତ౵GÁ͉Ȅڎࡢఘyj͉་ତxi͈౵଼ͬ໦̳͂ͥn ষࡓα·Πσ ́ນ̳ȃࡢఘତm͉ഐܽ

஖೰̯ͦͥȃ

૶͈஖఼

֒ഥഎͺσΌςΒθ͉୆໤͈ૺاͬ࿅༩̱̹डഐا ͺσΌςΒθ̜́ͥȃ୆໤͉ତ୷ଲయ̹ͩ̽̀ͅȄਬ౬

͈ಎ̥۪ͣޏͅഐࣣ̱̹͈̦͜୆̧ॼͤȄഐ̧ࣣ̞́̈́

͈͉͜ൕఋ̯̞̩ͦ̀^7ȫȃ֒ഥഎͺσΌςΒθ͈ίυΓ

ΑͬFig.2ͅা̳̦Ȅ֒ഥഎͺσΌςΒθ̴͉́͘Ȅഐ

൚̈́ࡢఘତ̥ͣ̈́ͥ੝ܢਬ౬ͬैͥȃ੝ܢਬ౬͈ڎࡢఘ

͈௺଻Ȫ་ତ͈౵ȫ͉၄ତͬঀ̽̀ρϋΘθͅࠨ೰̯ͦ

ͥȃষͅڎࡢఘ͈ഐ؊ഽȪ࿒എ۾ତȫͬບث̱Ȅഐ؊ഽ

̦̞ࣞࡢఘͬষଲయͅঊఃͬॼ̳૶̱͂̀஖఼̳ͥȃ̭

̧͈͂ਬ౬̱͈͂̀ఉအ଻ͬږ༗̳̹ͥ͛ͅȄഐ؊ഽ̦

ड̞ࣞ͜ࡢఘͬ஖఼̳͈̩ͥ́̈́ഐ؊ഽ͈̞ࣞࡢఘ̦ږ ၚഎͅ஖͊ͦͥخෝ଻̦̩ࣞ̈́ͥσȜτΛΠσȜσͬဥ

̞̹ȃΫΛΠΑΠςϋΈGÁ͉૶̱͂̀3ࡢఘͬ஖఼

̳̦ͥȄ৘ତ౵GÁ͉ষͅ੆͓ͥౙ༰଻ୃܰ໦ື࢐ए

༹^:ȫͬनဥ̱̞̹̀ͥ͛Ȃ૶̱͂̀4ࡢఘͬ஖఼̳ͥȃ

Fig.1 Flow of genetic algorithm

࢐ए༹!

ΫΛΠΑΠςϋΈGÁ͉֒ഥঊႥ͈ಎ͈࢐एպ౾ͬ

၄ତͤ͢ͅࠨ͛Ȅ3͈̾૶̷̸͈͈ͦͦ֒ഥঊႥ͈࢐ए

3

מὬȆזઐഓ჊ȇ֒ഥഎͺσΌςΒθͥ͢ͅݽႻ၌ףडఱݽ஑͈৽ါ࿒͈࠿൦

պ౾ո͈ࣛ֒ഥঊͬ࢐̳̭۟ͥ͂ͤ͢ͅȄ૧̱̞3͈̾

ࡢఘȪঊȫͬ୆̲ͥȃ࢐एպ౾ͬໝତ༹༷̜̦৾ͥͥ͜Ȅ

ུࡄݪ͉́࢐एպ౾͉2ؿਫ਼̱̹͂ȃ

৘ତ౵GA͈࢐ए༹༷̱͉̞̩̥͂̀̾೹մ̯̞ͦ̀

̦ͥȄུࡄݪ͉́ౙ༰଻ୃܰ໦ື࢐ए^9ȫ:ȫͬनဥ̱̹ȃ

༹̭͈༷͉́૶̱͂̀4ࡢఘͬ஖఼̱Ȃ2๔࿒͂3๔࿒

͈૶ࡢఘȪၰ૶͂ࡤ͐ȫ ͬࠫ͐ೄ஌͈ਔ༏ͅୃܰ

໦ືͅਲ̽̀ˎ͈̾ঊ ͬୃܰ၄ତͤ͢ͅږၚഎͅ୆

଼̳ͥȃ

ȁ ȁȁ Ȫ2ȫ

̭̭́Ȅȁ

ȁ ȁȁ Ȫ3ȫ

ȁ ȁ

̜́ͥȃ̹͘ȂD͉ల4͈૶̥ͣၰ૶ͬࠫ͐ೄ஌͒ئͧ

̱̹଒ೄݻၗ́Ȅ ͉ၰ૶ͬࠫ͐ೄ஌ͅೄ࢐̳ͥ໐໦ߗ ۼ͈ୃܰೄ࢐ܖೲα·Πσ̜́ͥȃn͉୭ࠗ་ତ͈ତ́Ȅ ЄȄϽ͉໦८ ͈ୃܰ၄ତ̽̀͢ͅ஖೰̯ͦͥȃ

లˏ͈૶͉Ȅၰ૶ͬࠫ͐ೄ஌͂ೄ࢐̳༷͈ͥ࢜Ȅೄ

஌̥͈ͣ༊֊ͬࠨ͈͛ͥͅঀ̠ȃ̱̹̦̽̀లˏ͈૶

͉୆଼̯ͦͥঊ̦ၰ૶͈௺଻ͬೄ୪എ̧֨ͅࠑ̪͈́

͉̩̈́Ȅ̞̠̈́ͦ͊࿹̹ͦ঩ৗͬ঵̾ఈ૽͈ࠬͬई̶

̀Ȅఉအ଻ͬ༗̾൱̧̦̜ͥȃˎ͈̾ঊ͉ၰ૶͈ಎത

ͅచ̱̀തచઠͅࠨ೰̯ͦͥȃ̭̭́ဥ̞ͣͦͥୃܰ

໦ື͉໹޳౵̦ΔύȄດ੔༊ओ ͉හփͅ୭೰̯

ͦȄດ੔༊ओͬఱ̧̈́౵͂ͥ͂ͅఉအ଻̦̩̦ࣞ̈́ͥਓ

௵̦ಁ̩̹̈́̽ͤȄං̥̹̳̭̦̜ͣͦ̈́̽ͤͥ͂ͥȃ ȁ࢐ए͉m/3ٝ߫ͤ༐̱̀mࡢ͈ঊރͬ୆଼̳ͥȃഐ

ࣣ଻͈̞ࣞࡢఘ͉ةഽ͜૶̱͂̀஖఼̧̯̭̦ͦͥ͂ܳ

ͥȃଲయତ̦ૺ͚͂൳̲૶ͬ঵̾ঊ̦௩̢̀ਬ౬̱͂̀

͜ఉအ଻̦೩ئ̱̀Ȅޫఱ౵Ȫޫਫ਼ٜȫͅۿ̭̦̜ͥ͂

͈ͥ́ಕփ̦ຈါ̜́ͥȃ ඏட་։

ΫΛΠΑΠςϋΈGÁ͉Ȅڎଲయ̤̞̀ͅڎࡢఘ͈

ڎ֒ഥঊ̞֚̾̀ͅအ၄ତͤ͢ͅږၚഎͅඏட་։̥̓

̠̥ͬࠨ೰̱Ȅڂ൚̷̧̳͉͈ͥ͂֒ഥঊ͈౵̦1͈͂

̧͉2ͅȄ2̧͈͉͂1ͅ฽ഢ̵̯ͥȃ৘ତ౵GÁ͉Ȅ ڎଲయ̤̞̀ͅ஠͈̀ࡢఘ͈ڎ་ତ̞֚̾̀ͅအ၄ତͅ

ͤ͢ږၚഎͅඏட་։̥̠̥̓ͬࠨ೰̳ͥȃඏட་։ͅ

ڂ൚̱̹ࡢఘ͈་ତ͈౵͉૧̹ͅ၄ତͤ͢ͅρϋΘθͅ

୭೰̳ͥȃඏட་։̧̦ܳͥږၚ͉ထ͛୭೰̱̤̩̦̀Ȅ

ུࡄݪ͉́2/211̱̹͂ȃ ଲయ࢐య!

ᰴ਎ઍߦᱷߔ୘૕ߣߒߡ㧘ⷫߣ↢ᚑߐࠇߚሶ߆ࠄߥ

ࠆኅᣖߩਛ߆ࠄᦨ⦟ߩ3୘ࠍㆬ߱ᣇᴺ߿㧘ⷫߣሶߩ㧞

਎ઍߩో૕߆ࠄᦨ⦟ߩ୘૕ࠍ㗅ߦㆬ߱ᣇᴺ㧘ⷫ㓸࿅ߩ ㆡᔕᐲߩૐ޿୘૕ߣሶ୘૕ࠍ౉ࠇᦧ߃ࠆᣇᴺߥߤ㧘޿

ߊߟ߆ߩ਎ઍ੤ઍࡕ࠺࡞߇ឭ᩺ߐࠇߡ޿ࠆ߇^21ȫ㧘ᧄ⎇

ⓥߢߪࡆ࠶࠻ࠬ࠻࡝ࡦࠣGAߢ߽ታᢙ୯GAߢ߽න⚐

ߦ㧘↢ᚑߐࠇߚሶࠍⷫߦઍࠊߞߡᰴ਎ઍߦᱷߔᣇᴺࠍ ណ↪ߒߚޕ

डഐ౵Ȫडఱ౵ȫ

ထ͛߫ͤ༐̳ଲయତͬ୭೰̧̱̤̀Ȅ̴͘ڎଲయ͈ಎ

́डഐ౵Ȫडఱ౵ȫ͂̈́ͥଲయडഐ౵Ȫଲయडఱ౵ȫͬ

ݥ͛Ȅडࢃͅ஠͈̀ଲయडഐ౵͈ಎ̥ͣडਞഎ̈́डഐ౵

Ȫडఱ౵ȫ͂̈́ͥࡢఘȪडഐٜȫͬ஖͐ȃ ႀ֖ٸ་ତ͈ե̞

ΫΛΠΑΠςϋΈGÁ͉Ȅ͂ͤං̧͓ͥ་ତ͈ํս

͉֒ഥঊႥ͈ΫΛΠତ̽̀͢ͅ୭೰̯̞̥ͦ̀ͥͣ࢐ए

ً͈೾́་ତ̦ႀ֖ٸͅ੄̭͉̞̦ͥ͂̈́Ȅ৘ତ౵GA

͉́Ȅထ͛୭೰̯̹ͦ་ତႀ֖͈ޏٮັ߃ͅഐ؊ഽ͈

άȜ·̦̜ͥાࣣȄଲయତ̦ఉ̩̈́ͥ͂୆଼̯̹ͦঊ͈

་ତ͉ႀ֖ٸͅ੄̭̦̜ͥ͂ͥȃ̭͈̠̈́͢ાࣣ͈৾ͤ

ե̞̞̾̀ͅ3༹͈༷̞̾̾̀ͅ࠿൦̱̹ȃ

A༹ȇঊࡢఘ͈̜ͥ་ତ౵ ̦୭೰̯̹ͦ་ତ͈ႀ֖

಼̢̹ͬͣȄ૶͉͂۾߸̩̈́٨֚͛̀အ၄ତͤ͢ͅȄ୭

೰̯̹ͦ་ତ͈ႀ֖ඤ̠̈́ͥ͢ͅͅ ͈౵ͬࠨ͛ͥȃ B༹ȇঊࡢఘ͈̜ͥ་ତ౵ ̦୭೰̯̹ͦ་ତ͈ႀ

಼̢֖̹ͬͣȄ಼̢̹ݻၗ͂൳̲ၾ̺̫Ȅႀ֖͈ޏٮ

̥ͣႀ֖ඤ͒୬ͤ༐̳ȃ̳̻̈́ͩȄ་ତ ͈ํս̦

̧̜́ͥ͂Ȅ୆଼̯̹ͦঊ͈ ̦႕̢͊

ͤ͢͜ఱ̧̞౵̺̹̳̽͂ͥ͂Ȅ૧̱̞ ͉ষ͈̠͢

ͅ٨͛ͥȃ

ȁ Ȫ4ȫ

ତ౵৘ࡑ

৘ତ౵GA̞̾̀ͅȄA༹ȄB༹͈࿹Ⴆͬ಺औ̳̹ͥ

͈֚͛̾ͅαϋΙζȜ·࿚ఴ̞̾̀ͅ๤ڛ৘ࡑ࣐ͬ̽

̹ȃαϋΙζȜ·࿚ఴ̱͉͂̀Ȅఉအ଻ͬບث̳̹ͥ͛

ͅఉ༰଻۾ତ̜́ͥRastrigin۾ତͬဥ̞̹^22ȫȃ

ȁȁȁȁȁȁ ȁȁȁ Ȫ5ȫ

Rastrigin۾ତ͈஠ఘഎ̈́အঊͬ౶̹ͥ͛ͅȄ୭ࠗ་ତ

̦ˎࡢȪn=3ȫ͈ાࣣ̞̾̀ͅȄ་ତx₂Ȅx3ͅచ̳ͥ۾

ତ౵͈་൲ͬFig.3ͅা̳ȃႀ֖ඤͅఉତ͈άȜ·̦ం

ह̱̞̦̀ͥȄ̞ࣞ౵͈άȜ·͉ႀ֖͈ਔ༏ັ߃̜ͥͅ

̭̦͂໦̥ͥȃ̭͈̠͢ͅఉତ͈άȜ·̦̜ͥ۾ତ͈ા

ࣣ͉Ȅडഐٜ̱͂̀ౝऔ̯̹ͦ౵͉ޫਫ਼ٜȪޭఱ౵ȫͅ

ۿ̳̞͈ͤ́͞Ȅ૯͈डഐٜȪडఱ౵ȫͬං̹͉ͥ͛ͅ

ਬ౬̱͈͂̀ఉအ଻̦ਹါ̈́ͥͅȃA༹͂B༹͈ఉအ

଻ͬ๤͓̹ͥ͛ͅତ౵৘ࡑͬ৘ঔ̱̹ȃུ৘ࡑ͉́Ȅౙ

༰଻ୃܰ໦ື࢐ए͈ດ੔༊ओͬ1.56Ȅࡢఘତ41Ȅ་ତ3Ȅ ଲయତ41Ȅඏட་։ၚ2/2111͂୭೰̱Ȅ̷̸ͦͦ4ٝ

͈দ࣐ࠗॳ࣐̹ͬ̽ȃ

Fig.2 Rastringin function of x1 and x2

Fig.4͂Fig.5̷̸͉ͦͦA༹͂B༹ͥࠗ͢ͅॳࠫض́Ȅ

ڎଲయ͈ଲయडఱ౵ͬ଎া̱̹͈̜́ͥ͜ȃडਞഎ̈́ड ఱ౵Ȫडഐٜȫͅൢో̳ͥଲయ͉ڎদ࣐ࠗॳ́։̦̈́ͥȄ

̴̞͈ͦদ࣐́͜डਞഎ̈́डఱ౵̱͉͂̀91ͅ߃̞౵

̦ං̤ͣͦ̀ͤȄA༹͂B༹ͅ࿹Ⴆ͉̞̈́ȃ̭͈࿚ఴ͈

ાࣣ͉41ଲయ̩̞͈ͣ́ࠗ͘ॳ̳ͬͦ͊Ȅडఱ౵Ȫड ഐٜȫͬං̧̭̦ͥ͂́ͥȃ̱̥̱Ȅ་ତ̦௩̢ͥ͂ଲ యତͬఱ̧̩୭೰̱̞̈́͂डఱ౵Ȫडഐٜȫ͉ංͣͦ̈́

̩̈́ͥȃ

Fig.3 History of maximum value for each generation by A method

Fig.4 History of maximum value for each generation by B method

Fig.6͂Fig.7͉ȄA༹ ͂B༹ ͅ ̤ ̞ ̀Ȅ21Ȅ31Ȅ41 ଲయ࿒̤̫ͥͅ41ࡢఘ͈໦ືͬx₂Ȅx3͈जດͅা̱̀

̞ͥȃÁ༹͉ଲయ̴̥̥ͩͣͅႀ֖ඤͅࢩ̩໦ື̱

̞͈̀ͥͅచ̱ȄB༹͉́ଲయ̦̩̜ࣞ̈́ͥ͂ͥ઀̯̈́

ႀ֖ͅਬಎ̱̞̭̦̀ͥ͂໦̥ͥȃ̳̻̈́ͩB༹͉́Ȅ ࡢఘ̦ޫਫ਼എ̈́άȜ·ਔ༏ͅਬ̧̞͈̽̀̀ͥ́͘Ȅఉ အ଻͈۷ത̥͉ͣA༹̦࿹̢̞̞ͦ̀ͥ͂ͥȃఉအ଻

ͬা̳ঐດ̱͂̀་ତ͈໦८ͬ๤ڛ̳ͥ͂Table 2͈͢

̠̈́ͤͅȄA༹͉ଲయۼ͈ओ̦ઁ̞͈̈́ͅచ̱̀ȄB༹

͉21ଲయ࿒ͅ๤͓̀31Ȅ41ଲయ࿒͉́2ࠥ઀̯̩̈́̽

̀Ȅ་ତ͈८̦ͣ͊ͤ઀̯̩Ȅఉအ଻̦అ̞̈́ͩͦ̀ͥ

̭͂ͬা̱̞̀ͥȃ

Fig.5 Distribuion of variables x1 and x2 at three generations by A method

Fig.6 Distribuion of variables x1 and x2 at three generations by B method

৘ତ౵GAུ̞࣐̹̾̀̽ͅତ౵৘ࡑ͈ࠫض͉A༹

͂B༹͕͖́൳̲̠̈́͢डఱ౵Ȫडഐٜȫͬං̞̦̀ͥȄ ఉအ଻̞̠͂۷ത̥͉ͣA༹̦࿹̞ͦ̀ͥ฻౯̯ͦͥ

͈́Ȅոئ͉́A༹ͬनဥ̱̹ȃ

̧͘࿌ݽ஑͈डഐ஑߿

Ȫԅȫȁ৘ତ౵GA͂ΫΛΠΑΠςϋΈGA͈๤ڛ ୭ࠗ་ତ

௙Πϋତ291Πϋ̧͈͘࿌ݽ஑ͬచયͅාۼ၌ףڣ̦

डఱ͂̈́ͥ஑߿͈৽ါ࿒ͬȄGAͬဥ̞̀ౝऔ̳̭ͥ͂

ͬদ͙̹ȃ୭ࠗ་ତ͉஑ಿLȄ஑໙BȄْࠗݎକdȄ஑

ఘಎ؇౯࿂߸ତCmȄ຾૤պ౾lcbȄْ̤͍ࠗ͢ેఠ̤ͅ

̫ͥ஑ਉକ஌͈වৣڙഽiÉ̜ͥȃ̭͈ͦͣ୭ࠗ་ତ͉

Oortmerssen^23ȫͥ͢ͅ೷ࢯଔ೰৆ͅဥ̞ͣͦͥ་ତ̜́ͥȃ

5

מὬȆזઐഓ჊ȇ֒ഥഎͺσΌςΒθͥ͢ͅݽႻ၌ףडఱݽ஑͈৽ါ࿒͈࠿൦

࿒എ۾ତ

୭ࠗ་ତͬဥ̞̀GA͈࿒എ۾ତ̜́ͥාۼ௙၌ףڣ

ͬଔ೰̳ͥ৆ͬষ͈̠͢ͅ൵̞̹ȃ ȁාۼ௙၌ףڣ

ȁȁȁɁාۼ௙ਓවڣȽාۼ௙঑੄ڣȁȁȁ Ȫ6ȫ ȁාۼ௙ਓවڣ

ȁȁȁɁ໹޳ݿثȿාۼ௙ݽڕၾ ȁȁȁ Ȫ7ȫ ݿث͉ݿਅ͞ܬ୯Ȅ̷͈ఈ͈২ٛૂସ̽̀͢་൲̳ͥ

̦Ȅݽ஑ݽުͥ͢ͅාۼ௙ਓවڣ͈ॳ೰͉ͅ໹޳ݿثͬ

୭೰̱̀Ḙ̏ͦͅ௙ݽڕၾͬ઺̲̀ݥ̭̱̹͛ͥ͂ͅȃ

ාۼ௙ݽڕၾ͉੄࣎ˍٝ൚̹͈ͤݽڕၾͅාۼ੄࣎ٝ

ତͬ઺̲̹͈̱̹͂͜ȃ ȁාۼ௙ݽڕၾ

ȁȁɁˍ࣎٬൚̹͈ͤݽڕၾȿාۼ੄࣎ٝତ ȁȁ Ȫ8ȫ ݿث̧͘͞࿌ݽު͈ාۼ੄࣎ٝତȄݽા؉໘শۼ൝͉

3112ාഽ͈ݽުฒ੥^23ȫ൝ͬ४ࣉ̱̀ͅȄոئ͈̠͢ͅ

୭೰̱̹ȃ

ݿث̞͉̾̀ͅȨ̏͘࿌ݽު́ఉ̩ݽڕ̯ͦͥ΍ϋζȄ ͺΐͬݽڕచયݿ̱͂̀Ȅ໹޳ݿثͬ81Ȫ׫/kgȫ͂୭

೰̱̹ȃාۼ੄࣎ٝତ͉Ȅݽުͬ߃٬̥Ȅ̹͉͘׿ဢ́

࣐̠̥ͤ͢ͅఱ̧̩։̦̈́ͥȄུࡄݪ͉́׿ဢݽު́ා

ۼ੄࣎ٝତͬ7̱̹ٝ͂ȃˍ࣎٬൚̹͈ͤݽڕၾ͉Ȅݿ

ாယୟ͈86%͈ݽڕၾͬ׋เ஑ͥ͢ͅ2͈ٝ࿶௣ၾ͂

̱Ȅ࿶௣ٝତͬ8̱ٝ͂̀Ȫ9ȫ৆́ݥ͛ͥȃ ȁˍ࣎٬൚̹͈ͤݽڕၾ[t]

ȁȁɁ 1.86[ ] ȿ[ݿாယୟȶ] ȷȿ˓ ȁ Ȫ9ȫ ݿாယୟ͉஑߿৽ါ࿒൝̥ͣȪ:ȫ৆́߃য̳ͥȃ ȁݿாယୟ

ȁȁɁ 1.3 ȿC_bȿLȿBȿDȽ 31ȶ ȷ ȁȁȁȁ Ȫ:ȫ

̭̭́ȄD͉૬̯ȄCb͉༷ࠁ߸ତ̜́ͥȃCb͉ෳକ ၾϚͤࠗ͢ॳ̱̹ȃD̤͍͢Ϛ͉ݽ஑͈ΟȜΗͤ͢Ȅ

Fig.8̤͍͢Fig.9ͅা̳̠͢ͅȄݎକd̤͍͢௙Πϋ

ତT͈۾ତ̱͂̀ٝܦ৆Ȫ21ȫȄȪ22ȫ৆ͤ͢ͅଔ೰̳ͥȃ ȁȁ ȁȁ Ȫ21ȫ ȁ Ȫ22ȫ

Fig.7 Relationship between depth and draft

Fig.8 Relationship between displacement and gross tonnage

ষͅȄාۼ௙঑੄ڣ͉ႻೈȄීၳ๯Ȅࡘثરݕ๯Ȅݽ Ⴛאު๯̷̤͍͈͢ఈȪ̢̯యȄݽߓȆݽ஑͈༞ਘ๯Ȅ

༗ࡏ๯̈́̓ȫࣣ̱̹ͬࠗ߄ڣ̱͂̀ȄȪ23ȫ৆ͤ͢ݥ͛ͥȃ ȁ[ාۼ௙঑੄ڣ]

ȁȁɁ[ݽႻคષࡔث]ȼ[ݽႻאު๯] Ȫ23ȫ ȁ[ݽႻคષࡔث]

ȁȁɁ[Ⴛೈ]ȼ[ࡘثੲݕ๯]ȼ[ීၳ๯]

ȁȁȁȁȼ[̷͈ఈ͈ࠐ๯] Ȫ24ȫ

ུࡄݪ͉́௙ΠϋତTͬ291Πῧܰ೰̱̞̹̀ͥ

͛Ȅݽ஑͈৽ါ࿒̦་ا̱̀͜઺ழ֥ତ͉͕͖֚೰͂ࣉ

̢̀ȄႻೈ͉ාۼ௙ਓව͈51ɓ͂୭೰̱̹ȃ̹͘Ȅݽ Ⴛאު๯͜ාۼ௙ਓව͈21%͂୭೰̱̹ȃ̷͈ఈ͈ࠐ

๯͉ݽႻคષࡔث͈41%̱̹͂ȃ

ȁ[Ⴛೈ]Ɂ[ාۼ௙ਓව] ȿ 1.5ȁ Ȫ25ȫ ȁ[ݽႻאު๯]Ɂ[ාۼ௙ਓව] ȿ 1.2 Ȫ26ȫ ȁ[̷͈ఈ͈ࠐ๯]Ɂ[ݽႻคષࡔث]ȿ 1.4ȁȁ Ȫ27ȫ ȁ

ࡘثੲݕ๯͉஑ثͬੲݕාତ́ڬ̹͈̽́͜Ȅུࡄ ݪ͉ੲݕාତͬ26ා͂ب೰̱̹ȃ஑ث͈ଔ೰͉ͅȪ29ȫ

৆ͬဥ̞̹ȃK2ȡK₅͉৘஑ثͬ߃য̳̠ͥ͢ͅ಺ା̱

̹߸ତ̜́ͥȃ

ȁ[ࡘثੲݕ๯]Ɂ[஑ث]/[ੲݕාତ] Ȫ28ȫ Table 1 Comparison of variance between A method and B method

variables x1 x2

method A method B method A method B method

10^th generation 5.34 4.58 5.93 4.47

20^th generation 8.02 0.14 5.66 0.14

30^th generation 10.14 0.17 6.42 0.28

ȁ Ȫ29ȫ

Ȫ29ȫ৆ֲ͈༏ల2͉ࣜ஑ڔࢥैͅ๤႕̳ͥࢥ๯́Ȅ ٸโ࿂ୟ͂ࢥତ̦̥̥ͥ஑ਉ๶͈஑ಿͅ୸͛ͥڬࣣͬা

̳B/Lͬঐດ̱̞͂̀ͥȃडࢃ͈͉ࣜඤ௡ࢥম͞୭๵

̈́̓Ȅ஑஠ఘ͈ఱ̧̯ͅ۾߸̳ͥࠐ๯Ȫࢥ๯Ȅ୭๵๯̈́

̓ȫͬນ̱̞̀ͥȃ৽ܥثڒ͉੄ႁ͕͖ͅ๤႕̳ͥ͂߃ য̱̹ȃ༞ܥ̈́̓͜৽ܥ͈ఱ̧̯ͅ๤႕̳̱ͥ͂̀Ȅ߸

ତK₃́಺ା̱̹ȃ

BHP͉࣎٬௸ႁV͈শ͈஑ఘ೷ࢯRt͂ଔૺ࢘ၚϽ͢

ͤȄȪ2:ȫ৆ͤ͢ݥ͛ͣͦͥȃ

ȁ Ȫ2:ȫ

ݽ஑஑߿ͬచય̱̀ͅȄ۰ౙ́๤ڛഎഐဥ଻̦̞ࣞ೷

ࢯଔ೰༹̱͂̀Ȅvan G.Oortmerssen^23ȫ͈ଔ೰৆ͬဥ̞̹ȃ

̹̺̱Ȅ̞̩̥͈̾ݽ஑஑߿̞͈̾̀ͅକ௑৘ࡑࠫض͂

๤ڛ̱̀Ȅࡔა໲̜ͥͅ߸ତc₄͈ࣜͬજ̞̹Ȫ31ȫ৆

ͬनဥ̱̹ȃ

ȁ ȁȁȪ31ȫ

̭̭́ȄϚ͉ෳକၾȄS͉૫କ࿂ୟȄЇ͉ၠఘྟഽȄ Fn͉έσȜΡତȄRn͉τͼΦσΒତ̜́ͥȃm,c2,c₃,c₅

͉L/BȄCp൝͈஑߿ΩριȜΗ͈۾ତ̱͂̀ນ̯ͦͥ

23ȫȃ૫କ࿂ୟS͉Ȫ32ȫ৆ͤ͢ͅ߃য̱̹ȃ

ȁ ȁȁȁȁȁȁȁȁȁȁȁȁ ȁȁȪ32ȫ

̧͘࿌ݽ஑̞̾̀ͅȄȪ31ȫ৆͈ଔ೰౵͂ٝၠକ௑৘

ࡑࠫض͈๤ڛͬFig.:ȪaȫͅȄݽުႯਠ஑̞͈̾̀ͅ๤

ڛͬFig.:Ȫbȫͅা̳̦Ȅଔ೰౵͉৘ࡑ౵̩֚͂͢౿̱

̞̀ͥȃఈ͈ତୗ͈ݽ஑஑߿̞͈̾̀ͅ๤ڛ̥ͣȄଔ೰

৆Ȫ31ȫུ͉ࡄݪͅঀဥ̧́ͥ͂฻౯̱̹ȃ̤̈́Ȅଔૺ

࢘ၚ ͉1.7͂ب೰̱̹ȃ

Fig.9(a) Comparison of EHP between estimate and experiment for a fi shing vessel

Fig.9(b) Comparison of EHP between estimate and experiment for a training ship

ষͅීၳ๯̞̾̀ͅࣉ̢ͥȃීၳ๯͉ීၳક๯ၾͅී

ၳثڒͬ઺̲̹͈́͜Ȫ33ȫ৆ͤ͢ͅݥ͛ͣͦͥȃ ȁ[ීၳ๯]Ɂ[ීၳક๯ၾȪͰȫ]

ȁȁȿ[Aਹ࿳ثڒȪ׫/Ͱȫ] [׫] Ȫ33ȫ

̭̭͉́ȄAਹ࿳ثڒ֚ͬ೰͈41׫/Ͱ̱̹͂ȃීၳ

ક๯ၾ͉ීၳક๯ၚȄAਹ࿳͈ྟഽ Ȅ৽ܥ෯ႁBHP

̤͍͢௢࣐শۼͤ͢Ȫ34ȫ৆́ݥ͛ͣͦͥȃ [ීၳક๯ၾ]Ɂ[ීၳક๯ၚ]/

ȿBHPȪkwȫȿ[ාۼ௢࣐শۼȪhȫ] [Ͱ] Ȫ34ȫ

ීၳક๯ၚ͉2111 ȡ 3111kw·ρΑ͈ΟͻȜΔσ΀

ϋΐϋ͈৘ୡ̥ͣ1.3[kg/ȪkwȆhȫ]̱̹͂ȃ̹͘ȄA ਹ࿳͈ྟഽ͉ Ɂ 1.96[kg/Ͱ]̱̹͂ȃȁ

2͈ٝ࣎٬͉́Ȅݽાْ́ͬࠗ͘௸ႁV́Ȅ໹޳˒඾

ۼ́؉໘࣐̱࣎Ȅௌު͉ːˌ඾ۼ̱͂̀Ȅௌުಎ͈ීၳ

ક๯͉೰ڒ੄ႁ͈76ɓ͂ب೰̱̀Ȅْࠗ௸ႁ́࣎௢̱

̹শۼ۟ͅॳ̳ͥȃ֚ාͅ˒ٝ੄̳̱࣎ͥ͂̀Ȅාۼ௢

࣐শۼͬ5711শۼ̱̹͂ȃ ଷ࿩ૄ࠯

ࠗॳࠫض̦৘षഎ̈́౵̠͂̈́ͥ͢ͅȄ୭ࠗ་ତ͈ํս

ͬئܱ͈̠͢ͅ୭೰̱̹ȃ

L=39~54 [m] B=7~8.6 [m] d=3~4.6 [m] C_m=1.97~1.:76 lcb=Ƚ 4.3~2.1 [%] iE=29~39.6 [deg.]

̹͘Ȅ৽ါ࿒̥ͣGMͬଔ೰̱Ȅ໘ࡔ଻ͬࣉၪ̱̀

GM͈नͤංͥํսͬ୭೰̱̹ȃਹ૤̯ࣞͬKGȄ຾૤

̯ࣞͬKBȄιΗΓϋΗȜ฼ࠂͬBM̳͂ͥ͂Ȅ

ȁ ȁȁȁȁȁȁȁȁȁȁȁȁȪ35ȫ

̜́ͥȃKGȄKBȄBM͉Ȫ36ȫ৆́߃য̱̹ȃ

Ȫ36ȫ ȁ

ྖशેఠ͈GM͈ئࡠ͉Ȅఱߜ^25ȫ͈ޗش੥ܱͅश̯

̞ͦ̀ͥݽ஑͈GM͈ํսͬ४ࣉ̱̹ͅȃષࡠ͉઺ͤ

૤౷͈۷ത̥ͣȄ஑͈؍ဝͦਔܢ̦࿩5ຟոષ̱͂̀Ȅ GM͈ํսͬȪ37ȫ৆͈̠͢ͅ୭೰̱̹ȃ

ȁ ȁȁȁȁȁȁȁȁȁȁȁȁȁȪ37ȫ

7

מὬȆזઐഓ჊ȇ֒ഥഎͺσΌςΒθͥ͢ͅݽႻ၌ףडఱݽ஑͈৽ါ࿒͈࠿൦

ࠗॳࠫض

ْࠗȪ࣎٬ȫ௸ႁ̦9ΦΛΠ͂21ΦΛΠȄ23ΦΛΠ

͈4ΉȜᾼ̞̾̀Ȅࡢఘତͬ61Ȅଲయତͬ2111Ȅඏ ட་։ၚˍ/211̱͂Ȅ৘ତ౵GÁ͉ດ੔༊ओ Ȅ

̴͉̞ͦ͜1.4̱͂̀ࠗॳ̱̹ȃ৘ତ౵GA͂ΫΛΠΑ

ΠςϋΈGAȄ̷̸ͦͦ3̴ٝ̾ࠗॳ̱̀Ȅාۼ௙၌ף

ڣ͈डఱ౵ͬ๤͓̹ȃࠗॳࠫضͬTable 3ͅা̳ȃ၌ף डఱ౵̷̸͈͈ͦͦ3͈ٝদ࣐͈ओ͉ȄΫΛΠΑΠςϋ ΈGA͈23ΦΛΠ͈ાࣣ͉࿩21ɓ͂ఱ̧̩Ȅ̷ͦոٸ

͉2~6%ոඤ̜́ͥȃ̹͘ȄΫΛΠΑΠςϋΈGA͢ͅ

ͥ၌ףडఱ౵͉஠͈̀஑௸̤̞̀ͅ৘ତ౵GA͈ࠫض͢

ͤ͜৹ۙఱ̧̞ȃ஑௸̦̩͕ࣞ̈́ͥ̓၌ף͉ઁ̩̈́̈́ͥ

̴̭͉̞͈͂ͦGÁ͜൳̲̜̹́̽ȃ

৘ତ౵GA͂ਲြ͈ΫΛΠΑΠςϋΈGÁȄ̷̸ͦ

͈ͦාۼ௙၌ף̦डఱ͂̈́ͥݽ஑஑߿͈৽ါ࿒ͬTable 4ͅা̳ȃུࠗॳ͉Ȅ௙Πϋତ̦֚೰̞̠͂ૄ࠯࣐́̽

̞̀ͥȃ̭͉ͦȪ22ȫ৆ͤ͢Ȅෳକၾ֚೰̞̠͂ૄ࠯͈

ئ́ාۼ௙၌ף̦डఱ͂̈́ͥ஑ಿ͞໙Ȅݎକͬݥ̭͛ͥ

͂̈́ͥͅȃ৘ତ౵GA͂ΫΛΠΑΠςϋΈGA͈ࠫضͬ

๤ڛ̳ͥ͂Ȅාۼ௙၌ף͉Fig.21ͅা̳̠͢ͅၰ৪͈

ओ͉઀̯̞ȃ஑߿́๤ڛ̳ͥ͂Ȅ஑ಿL͉ၰ৪ͅఱ̧̈́

ओ͉ࡉ̴ͣͦȄ୭೰̱̹ํս͈ષࡠ౵ͅ߃̞̦Ȅ஑໙B

͉ΫΛΠΑΠςϋΈGA͈༷̦ఱ̧̩Ȅݎକd͉ݙͅ৘

ତ౵GA͈༷̦ఱ̧̞ȃ̳̻̈́ͩȄ৘ତ౵GA͈ࠫض͉

ΫΛΠΑΠςϋΈGA͈ࠫضͤ͢͜L/B̦ఱ̧̩ȄB/d

̦઀̯̞஑߿̞̈́̽̀ͥͅȃ̭͈̠͢ͅȄ3͈̾GÁ

ං̹ͣͦ໙B͂ݎକd͉̥̈́ͤ։̦̈́ͥȄාۼ௙၌ף ڣ͈ओ͉઀̯̥̹̽ȃ̭͉ͦ࿒എ۾ତȪාۼ௙၌ףȫ̦Ȅ

ޭఱ౵̦ໝତంह̳ͥఉ༰଻۾ତ̜̹́ͥ͛ͅȄ3͈̾

GÁ་ତ౵Ȫ஑߿৽ါ࿒ȫ͉ͅओ։̦୆̲̹̦Ȅංͣ

̹ͦޭఱ౵Ȫडఱ၌ףڣȫ͈ओ̦઀̯̞̹̜͛́ͥȃ̳

̻̈́ͩȄޭఱ౵ٜ̦ͬ͂ͥఉତంह̳͈ͥ́Ȅਓ௵ٜȪड ఱ౵ȫͬං͈̦ͥඳ̱̞̦Ȅͤ͢ၻ̞ٜͬං̹͈ͥ͛ΜȜ σ̱͂̀GA͉ခဥ̢̜̞́ͥ͂ͥȃ

Fig.10 Comparison of fi shery profi ts of the optimum ships obtained by two GA methods

Table 2 The maximum profi t obtained by real coded and bit-string GA methods unit: thousand yen

Ship speed [kt] 8 10 12

Trial No. 1st 2nd 1st 2nd 1st 2nd

Real coded GA 29007 27471 21100 20838 8222 8164

Bit-string GA 29121 28917 22687 22302 10153 9140

Table 3 Principal particulars of the optimum ships and their profi ts

Ship speed [kts] 8 10 12

Method of GA Real coded Bit-string Real coded Bit-string Real coded Bit-string

L [m] 42.00 43.00 42.50 43.00 42.80 43.00

B [m] 6.05 7.20 6.55 7.20 7.25 7.20

d [m] 2.72 2.20 2.71 2.40 2.70 2.50

Cm 0.945 0.965 0.955 0.965 0.960 0.965

lcb [%] 0.21 -1.00 -0.74 -1.10 -1.02 -1.50

iE [deg.] 28.3 28.5 22.1 28.5 26.4 18.0

Cp 0.729 0.725 0.661 0.664 0.592 0.638

Rf [N] 6895 6539 10482 9804 14755 13737

Rw [N] 500 4614 7213 6374 17599 19602

Rt [N] 7395 11153 17696 16178 32354 33338

BHP [kW] 51 77 151 139 333 343

Total Catch [ton] 2723 2906 2726 2827 2729 2792

Income [10⁶ yen] 190.6 203.4 190.8 197.8 191.0 195.4

Fuel cost [10⁶ yen] 1.6 2.5 4.9 4.5 10.8 11.1

Profi t [10⁶ yen] 29.0 29.1 21.1 22.7 8.2 10.1

஑௸͈֑̞ͥ͢ͅ஑߿৽ါ࿒͈་اͬࡉͥ͂Ȅ஑௸̦

௸̩̈́ͥ͂஑ಿL͞໙B͉ະ་̥Ȅ̴̥ͩͅ઀̯̩̈́ͤȄ ݎକd͉ఱ̧̩̞̈́̽̀ͥȃFig.22ͅC_p͈๤ڛͬা̱̀

̞̦ͥȄ̴̞͈ͦGÁ͜஑௸̦௸̩̈́ͥ͂Cp͉઀̯

̩̈́̽̀Ȅ௮෨೷ࢯRwͬ઀̯̩̱̞̀ͥȃ༷֚Ȅݿᦺ

̦৹ۙ઀̯̩̹̈́ͥ͛ݽڕၾ͉ࡘͤȄਓව̦ࡘઁ̳ͥȃུ

ࠗॳ͉́Ȅݽڕၾ͉ݿᦺ͈͙ͅऒֲ̯ͦ̀Ȅ஑௸͈גޣͬ

ࣉၪ̱̞̞̀̈́ȃ̳̻̈́ͩȄ஑௸̦௸̞͂ݽા்̩ͅ಍̞

̀ݽުশۼ̦௩̢̀ݽڕၾ̦௩̢ͥȄ்̜̞͉̩ͥܦࢽ̱

̞̀ࣞݿث́คͦͥȄ͈̈́̓၌തͬࣉၪ̱̞̞̹̀̈́͛Ȅ

஑௸͈גޣ̦ഐ୨ͅບث̯̞̞͈ͦ̀̈́́Ḙ̏ͦͣͬࣉၪ

̳ͥ͂ͤ͢ఏ൚̈́ࠫض̦ංͣͦͥ͂এͩͦͥȃ

Fig.11 Comparison of Cp of the optimum ships obtained by two GA methods

̤̈́Ȅུࠗॳ႕͉́Ȅ৘ତ౵GA͂ΫΛΠΑΠςϋΈ GÁ͉ྶږ̈́࿹Ⴆ͉෇̥̹͛ͣͦ̈́̽ȃ

ȪԆȫȁීၳ࿳ثڒ͈גޣ

ࠗॳૄ࠯̈́̓

߃ ාȄࡔ ࿳ ث ڒ ͈ ࣞ ൯ ͅ ͢ ͤȄݽ ஑ ͅ ঀ ဥ ̯ ͦ ͥ ਹ࿳ثڒ͜ݢ൯̱̀ݽުࠐאͅ૬࣫̈́גޣͬݞ͖̱̀

̞ ͥȃ୶ ͈ ࠿ ൦Ȫԅȫ́ ͉ ਹ ࿳ ث ڒ ͬ41׫/Ͱ ͂ ̱

̹̦Ȅ211׫/ Ͱ ̱̹͂ાࣣͅාۼ၌ף̦डఱ͂̈́ͥ

஑߿̞̾̀ͅ৘ତ౵GÁ࠿൦̱̹ȃ࿒എ۾ତ͈ࠗॳ

৆͉ਹ࿳ثڒͬ211׫/Ͱ ͂་ࢵ̱̹ոٸ͉Ȫԅȫ͈

ા ࣣ ͂ ൳ ̲ ͂ ̱ ̹ȃ୭ ࠗ ૄ ࠯ ͂ ̱ ̀ȄȪaȫȁ ௙ Π ϋ ତTͬ ֚ ೰ ͈291 GT͂ ̱ ̹ ા ࣣȄȪbȫȁ ௙ Π ϋ ତ ͅ ଷ ࡠ ͬ ح ̢ ̈́ ̞ ા ࣣȄ͈3Ή Ȝ Α ͂ ̱ ̹ȃུ ࡄ ݪ ́

͉Ȅ௙ Π ϋ ତ ͂ ෳ କ ၾ ͉Ȫ21ȫ৆ ͅ ͢ ͤ2փ എ ͅ ۾

߸ັ̫̞͈ͣͦ̀ͥ́Ȅ௙Πϋତ֚೰̞̠̭͉͂͂ෳ

କၾ֚೰Ȅ̞̠̭̜͂͂́ͥȃ୭ࠗ་ତ͉Ȫaȫ͈ા

ࣣ ͉ ୶ ͈ ࠿ ൦Ȫԅȫ͂ ൳ ̲ ́ ̜ ͥ ̦ȄȪbȫ́ ͉ ༷ ࠁ

߸ତCbͬ་ତ̱͂̀೏ح̱̹ȃCb͈৾ͤංͥํս͉

ȁȁȁ1.6< Cb <1.86ȁ ȁȁȁȁȁȁȁȁȁȁȁȁȁȪ38ȫ

̱̹͂ȃ

ࠗॳࠫض

஑௸̦9Ȅ21Ȅ23ΦΛΠ̞̾̀ͅȄ̷̸ͦͦ4͈ٝ

ࠗॳͬ৘ঔ̱̀Ȅ̷͈ಎ͈डఱ౵ͬनဥ̱̹ȃࠫضͬ

Table 5ͅা̳ȃාۼ၌ף̞̾̀ͅਹ࿳ثڒ̦41׫/Ͱ͈

ࠫض͂๤ڛ̳ͥ͂ȄFig.23ͅা̳̠͢ͅȄ௙Πϋତ֚೰

͈ૄ࠯͉́ਹ࿳ثڒ̦̩ࣞ̈́ͥ͂၌ף̦ઁ̩̈́̈́̽̀Ȅ 23ΦΛΠ͉́ζͼ΢Α͂̈́ͥȃ௙Πϋତ͈ଷࡠ̴͉ͬ

̳͂Ȅ9ΦΛΠ͈ાࣣ͉ਹ࿳ثڒ͈ࣞ൯ͬ΃ΨȜ̧́ͥ

̦Ȅ21Ȅ23ΦΛΠ͉́௙Πϋତ֚೰͈ાࣣ͂ओ͉̞̈́ȃ

஑߿͈๤ڛ̳ͬͥ͂ȄL/B͉Fig.24ͅা̳̠͢ͅȄ஑

௸̽̀͢ͅ։̈́ͥ་ا̱̞ͬ̀ͥȃ௙Πϋତ֚೰́ਹ

࿳ثڒ̦41׫/Ͱ͈ાࣣ͉஑௸̦௸̩̱̹̦̈́ͥ̽̀ͅ

L/B͉઀̯̩̞͈̈́̽̀ͥͅచ̱̀Ȅ௙Πϋତ֚೰́

ਹ࿳ثڒ̦211׫/Ͱ͈ાࣣ͉஑௸ͥ͢ͅ་ا͉ઁ̩̈́Ȅ

௙Πϋତܰଷྫ̱́ਹ࿳ثڒ̦211׫/Ͱ͈ાࣣ͉஑௸

̦௸̩̱̹̦̈́ͥ̽̀ͅఱ̧̩̞̈́̽̀ͥȃ༷ࠁ߸ତ C_b͈๤ڛͬFig.25ͅা̳ȃ஑௸̦௸̩̈́ͥ͂Ȅ̴̞ͦ

͈ાࣣ͜Cb͉઀̯̩̈́̽̀೷ࢯ೩ࡘͬ଎ͥ஑߿͂̈́̽

̞̀ͥȃਹ࿳ثڒ̦211׫/Ͱ̧͈͂Ȅ௙Πϋତܰଷྫ

̱͈ાࣣ͉௙Πϋତ֚೰͈ાࣣͤ͢͜Cb͉ఱ̧̩̈́̽

̤̀ͤȄݽڕၾ͈௩حͬ଎̞̽̀ͥȃ

Fig.12 Comparison of fi shery profi ts of the optimum ships under various conditions

Fig.13 Comparison of L/B of the optimum ships under various conditions

9

מὬȆזઐഓ჊ȇ֒ഥഎͺσΌςΒθͥ͢ͅݽႻ၌ףडఱݽ஑͈৽ါ࿒͈࠿൦

Fig.14 Comparison of Cb of the optimum ships under various conditions

௙Πϋତ͈ܰଷ̴͉̳ͬ͂௙Πϋତ֚೰͈ાࣣͅ๤͓

̀9Ȅ21ΦΛΠ͉́ෳକၾ͉ఱ̧̩̈́ͤȄ23ΦΛΠ́

͉઀̯̩̞̈́̽̀ͥȃ9Ȅ21ΦΛΠ͉́೷ࢯ͈௩ح͢ͅ

ͥීၳ๯͈௩ఱͤ͢͜Ȅ஑ͬఱ̧̩̱̀ݽڕၾͬ௩̳͞

༷̦၌ף̦ࡉࣺ̭͛ͥ͂ͬাऐ̱̞̀ͥȃ23ΦΛΠͅ

̈́ͥ͂ීၳ๯̦ఱ̧̨̩̳̈́ͤ̀Ȅ஑ͬ઀̵̯̩̰ͥͬ

ං̩̞̈́̈́̽̀ͥȃ ȁ

͂͛͘

ུࡄݪ͉́৘ତ౵GA͂ΫΛΠΑΠςϋΈGA͈3̾

͈GAͬဥ̞̀Ȩ̏͘࿌ݽ஑͈ාۼ၌ף̦डఱ͂̈́ͥ஑

߿͈৽ါ࿒ͬౝ̱̹॑ȃ̷͈ࠫضȄˎ͈̾GḀͣݥ͛

̹ͣͦ஑߿৽ါ࿒͉৹ۙ։̞̹̦̈́̽̀Ȅාۼ၌ף͉͕

͖൳೾ഽ̜̹́̽ȃ̭͉ͦޭఱ౵̦ໝତంह̳ͥఉ༰଻

͈࿒എ۾ତͅచུ̱̀ࡄݪ́नဥ̱̹GA̦ခ̜࢘́ͥ

̭͂ͬা̱̞̀ͥȃུࡄݪ͈৽࿒എ̜́ͥडഐ஑߿ౝݥ

͈͒GA͈ഐဥ଻̞͉̾̀ͅȄͤ͢ၻ̞஑߿ْ̳ͬࠗͥ

̹͈͛ခף̈́ͥ౶ࡉ̦ං̭̦ͣͦͥ͂ږ෇̧́Ȅඅͅ৘

ତ౵GA͉ίυΈρηϋΈ͜ယօ̜̹́ͥ͛Ȅ஑߿ْࠗ

͈੝ܢ࠿൦͉ͅခဥ̈́ΜȜσ̈́ͤͅං͈ͥ͂͜এͩͦͥȃ ȁུࡄݪ́࿒എ۾ତ̱͂̀৾ͤષ̬̹ාۼ၌ף͈ࠗॳ༹

̞͉̾̀ͅڎࣜ࿒͈ଔ೰ୈഽ͈࢜ષ͞ࡉೄ̱̳ͬͥຈါ

̦̜ͥȃ႕̢͊Ȅݽڕၾ͞ݿثȄࡔ࿳ثڒȄႻೈ͈̈́̓

ࠗॳ৆͉3112ා͈ࡣ̞঩ၳͅܖ̞̞͈̿̀ͥ́Ȅ࡛ે͂

͉̥̈́ͤેޙ̦։̞̈́̽̀ͥȃड߃͈ීၳ๯͈ࣞ൯ͅచ ੜ̳̹͉ͥ͛ͅȄ஑௸ͬಁ̩̳̭̦ͥ͂ड͜ခ༹༷࢘̈́

͈̠̜́ͥ͢ȃ̱̥̱Ȅུࡄݪ͉́஑௸͈ݿث͞ݽڕၾ

ͅݞ͖̳גޣ̈́̓ͬࣉၪ̱̞̞͈̀̈́́Ḙ͈̏ത̞̾ͅ

͉̀ࢵͅ࠿൦̦ຈါ̜́ͥȃ̹͘Ȅ௙Πϋତ͈ܰଷ͉ͬ

̴̳̭͂ͤ͢ͅȄ஑߿୭͈ࠗুဇഽ̦௩̱̀Ȅݽު၌ף

ͬષ̬̭̦ͥ͂خෝ̈́஑߿ͬࡉ੄̳̭͂͜خෝ̜́ͥȃ

̭͈̠͢ͅȄGAͬഐဥུ̱̹ࡄݪ͈਀༹͉࡛শതȄ

̜̞͉ͥ੿ြထ௶ͅܖ̞̿̀ഐ୨̈́࿒എ۾ତ͈ૄ࠯୭೰

࣐̠̭ͬ͂ͤ͢ͅȄ̷͈শത̤̫ͥͅडഐ஑߿͈ထ௶̦

̧́Ȅ૧̱̞ݽ஑஑߿͈ΪϋΠ̢͂̈́ͤͥ౶ࡉ̦ංͣͦ

͈ͥ͂͜ܢఞ̧́ͥȃ

Table 4 Principal particulars of the optimum ships and their profi ts calculated by the real-coded GA under the condition of high fuel price Condition of the gross

tonnage constant free

Ship speed [kts] 8 10 12 8 10 12

L [m] 39.90 41.40 42.50 42.20 42.70 42.80

B [m] 6.35 6.44 6.84 7.30 6.95 6.41

d [m] 2.94 3.09 3.06 3.27 2.89 2.59

Cb 0.640 0.578 0.536 0.700 0.620 0.575

Cm 0.930 0.895 0.947 0.945 0.945 0.945

lcb [%] -2.40 -1.40 -1.19 -0.484 -1.59 -1.69

iE [deg.] 27.1 26.4 23.8 23.0 22.1 22.0

Cp 0.688 0.646 0.566 0.741 0.626 0.608

∆[t] 488.3 488.3 488.3 722.8 545.0 419

Rf [N] 6796 10397 14720 8524 11112 13669

Rw [N] 2353 5363 16443 12389 8416 15027

Rt [N] 9149 15760 31163 20913 19527 28696

BHP [kw] 62 135 321 143 167 295

Total Catch [ton] 2666 2631 2638 4141 3062 2279

Income [10⁶ yen] 186.6 184.2 184.6 289.9 214.4 159.6

Fuel cost [10⁶ yen] 6.8 14.6 34.7 15.5 18.1 32.0

Profi t [10⁶ yen] 19.4 4.5 -27.9 32.7 7.2 -28.0

৫ȁৃ

߇ਗఱڠఱڠ֭ࢥڠࡄݪ֭հ൐੕ޗ਎Ȅݞ͍Ժ२֔௮

஑઎ോࡄݪਫ਼໹५ྶ૾ฎআͤ͢Ȅ৘ତ౵GA̞̾̀ͅ໲

ࡃ̈́̓ခף̈́ૂ༭̮ͬޗ਎̧̞̹̺̱̹͘ȃ̭̭ܱ̱ͅ

̀৫փͬນ̱̳͘ȃ̹͘ȄΫΛΠΑΠςϋΈGAͥ͢ͅ

ࠗॳ͈֚໐ͬ໦౜̱̩̹̀ͦ௾ު୆͈߬ࡔםਏ߯ۜͅ৫

̱̳͘ȃ

໲ȁࡃ

2ȫ କॲ௙ࣣࡄݪΓϋΗȜȄକॲࢥڠࡄݪਫ਼Ȫ3113ȫ.໹଼25

ාഽݽުܿ੅໐࣒ٛ׵ਬȄȶྶ඾͈ݽ஑௨ͬࣉ̢ͥȷȅ 3ȫ ༿ఆࢫ౳Ȅ२׆ંਏȪ3116ȫȅِ̦࣭͈੿ြ߿ݽ஑͈৽ါ

࿒ͅ۾̳ͥࡄݪȅ඾ུକॲࢥڠٛڠ੅࣒׵࣒ٛ׵ა໲ਬȄ 276-279ȅ

4ȫ କॲ௙ࣣࡄݪΓϋΗȜȄକॲࢥڠࡄݪਫ਼Ȫ3114ȫȅ໹଼26

ාഽݽުܿ੅໐࣒ٛ׵ਬȄȶྶ඾͈ݽ஑ݽުͬࣉ̢ͥȷȅ 5ȫ ܊ུधষȄ୞ઐ໌໲Ȅࣽୌ֚Ȅષ࿤ၦ௬Ȫ3113ȫȅ५࢛ࡇ

͈૧߿ࣣ̞ؗೲ̧֨࿌ݽ஑̞̾̀ͅȪల2༭ȫȅୌ໐௮஑

ٛٛ༭Ȅ215ȇ232-244ȅ

6ȫ କॲ௙ࣣࡄݪΓϋΗȜȄକॲࢥڠࡄݪਫ਼Ȫ3113ȫȅȶ̷̠֚

̧͍ڥ̫٠̱ݽ஑͈κΟσ୭ࠗ଎ै଼ͅ۾̳ͥࡄݪȷ༭࣬

੥ȅ

7ȫ չೳ୔঎Ȫ2::5ȫȅ֒ഥͺσΌςΒθ͈ܖயȝGA͈ඨͬ

ٜ̩ȝ,΂Ȝθ২ȅ

8ȫ ୞നၻ໹Ȅఆଳহ๤ࡣȄ઀५ਘ໹Ȫ2::8ȫȅΩΕ΋ΰڠ

͐֒ഥഎͺσΌςΒθ͈ܖய͂؊ဥȄ૩ཤ੄ๅڼ৆ٛ২ȅ 9ȫ ઀࿤ࢗȄ५ఆٗࢨȄܔఉ֚Ȫ3111ȫȅ৘ତ౵GA̷͈͂؊ဥȅ

૽ࢥ౶ෝڠٛধȄ26Ȫ3ȫȇ36:-377ȅ

:ȫ ઀࿤ࢗȄऎ൥ࢼȄ઀ႅਹ૞Ȫ2:::ȫȅౙ༰଻ୃܰ໦ື࢐ए UNDXͬဥ̞̹৘ତ౵GAͥ͢ͅ۾ତडഐاȅ૽ࢥ౶ෝڠ

ٛধȄ25Ȫ7ȫȇ2257-2266ȅ

21ȫऎ൥ࢼȄ઀࿤ࢗȄ઀ႅਹ૞Ȫ2::8ȫȅ֒ഥഎͺσΌςΒθ

̤̫ͥͅଲయ࢐యκΟσ͈೹մ͂ບثȅ૽ࢥ౶ෝڠٛধȄ 23Ȫ6ȫȇ845-855ȅ

22ȫᎢհ౶෗Ȅ२࿐࢕ํȄ໛זၦࢤȪ3113ȫ֒ഥഎͺσΌς Βθ̤̫ͥͅ৘ତ౵α·Πσນ࡛Ȅଲయ࢐యκΟσȄ༦ ਬ౬໦ڬ࢘ض͈࠿൦ȅThe Science and Engineering Doshisha UniversityȄXXȪYȫȅ

23ȫ van Oortmerssen, G.Ȫ 2:82ȫȅA Power Prediction Method and Its Application to Small ShipsȅInternational Ship Progress, 29 Ȫ22ȫȇ4:8-526ȅ

24ȫݽުฒ੥Ȫ3112ȫȅ෠ႅକॲજอ࣐ȅ

25ȫఱߜٗ૞ȅၑა஑ตࢥڠȪષےȫȅ٬໲൴Ȅ216ȅ