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Wyświetlanie 1-2 z 2
Tytuł:
Comparing heuristic methods’ performance for pure flow shop scheduling under certain and uncertain demand
Autorzy:
Nurprihatin, Filscha
Jayadi, Ester Lisnati
Tannady, Hendy
Powiązania:
https://bibliotekanauki.pl/articles/407243.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
forecasting
Monte Carlo simulation
standardized time
heuristic scheduling methods
Opis:
The main aim of this research is to compare the results of the study of demand’s plan and standardized time based on three heuristic scheduling methods such as Campbell Dudek Smith (CDS), Palmer, and Dannenbring. This paper minimizes the makespan under certain and uncertain demand for domestic boxes at the leading glass company industry in Indonesia. The investigation is run in a department called Preparation Box (later simply called PRP) which experiences tardiness while meeting the requirement of domestic demand. The effect of tardiness leads to unfulfilled domestic demand and hampers the production department delivers goods to the customer on time. PRP needs to consider demand planning for the next period under the certain and uncertain demand plot using the forecasting and Monte Carlo simulation technique. This research also utilizes a work sampling method to calculate the standardized time, which is calculated by considering the performance rating and allowance factor. This paper contributes to showing a comparison between three heuristic scheduling methods performances regarding a real-life problem. This paper concludes that the Dannenbring method is suitable for large domestic boxes under certain demand while Palmer and Dannenbring methods are suitable for large domestic boxes under uncertain demand. The CDS method is suitable to prepare small domestic boxes for both certain and uncertain demand.
Źródło:
Management and Production Engineering Review; 2020, 11, 2; 50-61
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Approximated fast estimator for the shape parameter of generalized Gaussian distribution for a small sample size
Autorzy:
Krupiński, R.
Powiązania:
https://bibliotekanauki.pl/articles/201165.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
estimation
generalized Gaussian distribution
standardized moment
approximated fast estimator
estymacja
oszacowanie
rozkład Gaussa
moment standaryzowany
Opis:
Most estimators of the shape parameter of generalized Gaussian distribution (GGD) assume asymptotic case when there is available infinite number of observations, but in the real case, there is only available a set of limited size. The most popular estimator for the shape parameter, i.e., the maximum likelihood (ML) method, has a larger variance with a decreasing sample size. A very high value of variance for a very small sample size makes this estimation method very inaccurate. A new fast approximated method based on the standardized moment to overcome this limitation is introduced in the article. The relative mean square error (RMSE) was plotted for the range 0.3-3 of the shape parameter for comparison with other methods. The method does not require any root finding, any long look-up table or multi step approach, therefore it is suitable for real-time data processing.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2015, 63, 2; 405-411
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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