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- W1853869105 abstract "Konkav Maliyetli Ulastirma Problemi (KMUP), gercek hayatta sik karsilasilan problemlerden birisidir. Dogrusal maliyetli problemlerin aksine, KMUP’de tasinacak miktar arttikca birim tasima maliyeti azalmaktadir. Bu tur problemlerde dogrusal olmayan maliyet fonksiyonundan dolayi klasik optimizasyon yontemleri ile en iyi cozume ulasmak mumkun olmayabilir. Son yillarda, genetik algoritmalar, tavlama benzetimi ve tabu arama gibi genel amacli sezgisel yontemlerin bu tur zor problemlerin cozumunde basariyla kullanildigi gorulmektedir. Bu calismada, KMUP icin genetik algoritmalara dayali bir karma sezgisel algoritma (karma GA) gelistirilmistir. Algoritmanin etkinligi, tedarikci ve musteri sayisinin 4 ile 40 arasinda degistigi ve rassal olarak uretilen 12 problem uzerinde incelenmistir. Gelistirilen karma GA, literaturde bu problem icin gelistirilmis olan tavlama benzetimi, esik kabulu ve dogrusal esik kabulu yontemine dayali sezgisel algoritmalar ile karsilastirilmistir. Karsilastirma sonucunda, gelistirilen karma GA ile dort problem icin cozum kalitesinde %0.3 ile %5 arasinda iyilesmenin oldugu gorulmustur." @default.
- W1853869105 created "2016-06-24" @default.
- W1853869105 creator A5053609850 @default.
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- W1853869105 date "2013-04-10" @default.
- W1853869105 modified "2023-09-26" @default.
- W1853869105 title "KONKAV MALİYETLİ ULAŞTIRMA PROBLEMİ İÇİN GENE-TİK ALGORİTMA TABANLI SEZGİSEL BİR YAKLAŞIM" @default.
- W1853869105 hasPublicationYear "2013" @default.
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