Öğrenme Etkili Çizelgelemede Maksimimum Gecikme ve Toplam Tamamlanma Zamanı Minimizasyonu

Bu çalışmada tek makineli çizelgelemede öğrenme etkisi analiz edilmiş, performans ölçütü olarak da toplam tamamlanma zamanı ve maksimum gecikme alınmıştır. Çalışmada problemin klasik (öğrenme etkisiz) durumda en iyi çözümü garanti eden Smith Algoritması [1] (maksimum gecikmeyi minimize etme kısıtı altında toplam tamamlanma zamanını minimize etme) ve Van Vassenhove ve Gelder algoritmasının [2] (toplam tamamlanma zamanı ve maksimum gecikmeyi aynı anda minimize etme) öğrenme etkili durumda optimal çözümü garanti etmediği gösterilmiştir. Problemleri çözmek için matematiksel programlama modelleri geliştirilmiştir.

Minimizing the Total Completion Time and Maximum Tardiness on a Scheduling with a Learning Effect

In this study; learning effect on single machine scheduling is analyzed of total completion time and maximum tardiness is taken as a performance criteria. This study shows that Smith Algorithm [1] (minimizing total completion time subject to minimum maximum tardiness) and Van Vassenhove ve Gelder algorithm [2] (minimizing total completion time and minimize maximum tardiness simultaneously) which guarantees the best solution in classical situation (without learning effect), cannot guarantee the best results in the situation with learning effect. Mathematical programming models are developed for solving these problems.

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