BOZULMA VE ÖĞRENME ETKİLERİ ALTINDAKİ BULANIK İŞLEM SÜRELERİ İLE ÇİZELGE TAMAMLANMA SÜRESİNİN EN AZA İNDİRİLMESİ

Year 2020, Volume: 31 Issue: 1, 1 - 17, 30.04.2020

Oğuzhan Ahmet Arık Mehmet Duran Toksarı

Abstract

Bu çalışma tek makine çizelgeleme
problemlerinde öğrenme ve bozulma etkileri altındaki belirsiz işlem sürelerini
incelemektedir. Öğrenme etkisi, bozulma etkisi ve işlem süresi gibi
parametrelerdeki belirsizliği ifade edebilmek için bulanık sayılar
kullanılmıştır. Çalışmaya konu olan ve belirsiz parametrelere sahip problemin
amaç fonksiyonu çizelge tamamlanma süresinin en aza indirilmesidir. Literatürde
birçok tek makine çizelgeleme problemi deterministik parametreler ile
incelenmiştir. Bu çalışmada ise karar vericilerin öğrenme ve bozulma etkileri
altındaki gerçek hayat tek makine çizelgeleme problemlerinin belirsizliği ile
başa çıkabilmelerine olanak tanıyacak bir metot tanıtılmaktadır. Problemin
karmaşıklığı nedeni ile birçok kısıt doğrusal değildir. Bulanık doğrusal
olmayan karma tam sayılı bir matematiksel model problemin çözümü için
önerilmiştir ve ayrıca bir sayısal örnek çalışma içerisinde verilmiştir.    

Keywords

Çizelgeleme, Bulanık, Bozulma, Öğrenme Etkisi

MINIMIZING MAKESPAN WITH FUZZY PROCESSING TIMES UNDER JOB DETERIORATION AND LEARNING EFFECT

Abstract

This paper
proposes a single machine/processor scheduling problem considering uncertain
processing times under job deterioration and learning effect. In order to
express uncertainty of parameters such as processing times, effects of
deterioration and learning, fuzzy numbers are used. The objective function in
this study is to minimize the makespan (maximum completion time) where the
parameters of the problem are fully uncertain. 
In the literature, many single machine scheduling problems have been
interested in deterministic model parameters such as processing times, due
dates and release dates.  This study
introduces a way for decision makers to cope with real life ambiguity and
imprecision in single machine scheduling problems with uncertain processing
time under uncertain effects of job deterioration and learning. Due to
complexity of the problem, most of constraints are non-linear. A numerical
example is illustrated and a fuzzy mixed integer nonlinear programming model is
proposed in this study.

Keywords

Scheduling, Fuzzy, Job Deterioration, Learning Effect, Mixed Integer Nonlinear Programming

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