Dinamik atölye tipi çizelgeleme problemine bir tavlama benzetimi yaklaşımı tabanlı simülasyon optimizasyonu

Year 2018, Volume: 24 Issue: 4, 665 - 674, 17.08.2018

Çağrı Sel Alper Hamzadayı

Abstract

Bu
çalışmada, bir üretim çizelgeleme problem ele alınmaktadır. Bu çizelgeleme
problemine atölye tipi bir üretim tipinde karşılaşılmaktadır. Üretim sistemi
sürekli iş gelişlerinin söz konusu olduğu kesikli dinamik sistemdir.
Çizelgeleme kurallarının birbirinden bağımsız şekilde kullanılmasının gerektiği
makine bozulmaları ve değişen teslim süreleri gibi bazı durumların
değerlendirilmesi için bir simülasyon modeli sunulmaktadır. En erken teslim
süresi, en kısa işlem süresi ve ilk giren ilk çıkar kuralı olmak üzere üç
çizelgeleme kuralı bu simülasyon modeline dahil edilmiştir. Dinamik sistemdeki
belirsiz çizelgeleri ortaya koymak için tavlama benzetimi sezgiseli tabanlı bir
simülasyon optimizasyonu yöntemi önerilmektedir. Sayısal analizlerde
çizelgeleme kurallarının ve önerilen tavlama benzetimi sezgiselinin
performansları simülasyon deneyleri kullanılarak kıyaslanmıştır.  Ortalama akış süresini ve ortalama gecikme
süresini en küçükleyen amaç fonksiyonları farklı seviyelerdeki atölye kullanım
oranı ve teslim süresi durumlarında incelenmiştir. Genel bir sonuç olarak,
önerilen tavlama benzetimi sezgiselinin en erken teslim zamanı ve ilk giren ilk
çıkar kurallarından daha iyi sonuç verdiği, en kısa işlem süresi kuralının en
iyi sonuçları sağladığı gözlenmiştir. Fakat tavlama benzetimi sezgiseli en kısa
işlem süresi kuralına çok yakın sonuçlara erişmektedir ve çözüm zamanının
kritik olduğu uygulamalarda kabul edilebilir bir hesaplama yükü getirmektedir.

Keywords

Atölye tipi çizelgeleme, Kesikli ve dinamik sistem, Tavlama benzetimi algoritması, Benzetim optimizasyonu, Çizelgeleme kuralları

A simulated annealing approach based simulation-optimisation to the dynamic job-shop scheduling problem

Abstract

In
this study, we address a production scheduling problem. The scheduling problem
is encountered in a job-shop production type. The production system is discrete and dynamic system in which jobs arrive continually. We introduce a
simulation model (SM) to identify several situations such as machine failures,
changing due dates in which scheduling rules (SRs) should be selected
independently. Three SRs, i.e. the earliest due date rule (EDD), the shortest
processing time first rule (SPT) and the first in first out rule (FIFO), are
incorporated in a SM. A simulated annealing heuristic (SA) based
simulation-optimisation approach is proposed to identify the unknown schedules
in the dynamical system. In the numerical analysis, the performance of SRs
and SA are compared using the simulation experiments. The objective functions
minimising the mean flowtime and the mean tardiness are examined with varying
levels of shop utilization and due date tightness. As an overall result, we
observe that the proposed SA heuristic outperforms EDD and FIFO, the well-known
SPT rule provides the best results. However, SA heuristic achieves very close
results to the SPT and offers a reasonable computational burden in
time-critical applications.

Keywords

Job-shop scheduling, Discrete and dynamic system, Simulated annealing algorithm, Simulation-optimisation, Scheduling rules

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