Gultekin Ozdemir

Quadratic quality loss functions and signal-to-noise ratios for a trivariate response

Abstract This paper extends Taguchis quadratic quality loss function (QQLF) and signal-to-noise (S/N) ratios to a trivariate case by considering correlations between all pairs of quality characteristics. Single static quality characteristics (QCHs) are classified as: (1) smaller the better (STB), (2) larger the better (LTB), and (3) nominal the best (NTB). Initially, Taguchi studied single-response models. Later Chang (1993) , Maghsoodloo and Chang (2001) , and Maghsoodloo and Huang (2001) obtained relationships for the bivariate response cases. Chang (1993) and Maghsoodloo and Chang (2001) developed relationships for cost coefficients of the bivariate QQLF and S/N ratios for the cases of (NTB, NTB), (STB, STB), and (LTB, LTB). Later Maghsoodloo and Huang (2001) developed relationships for the remaining cases, which are (STB, LTB), (STB, NTB), and (LTB, NTB). This paper extends the number of variates from two to three, which are correlated, and obtains relationships between cost coefficients to ensure that the cost matrix is positive definite (pd). Also, S/N ratios are developed for all combinations of trivariate responses.

Forecasting of Turkey natural gas demand using a hybrid algorithm

ABSTRACT The basis of the energy management constitutes the forecasting of the need for energy as much as accurate. In this study, a hybrid genetic algorithm-simulated annealing (GA-SA) algorithm based on linear regression has been developed and coded as software to forecast natural gas demand of Turkey. The linear models, which are constructed by using the amounts of natural gas consumption for years between 1985 and 2000 as dependent variable, and gross national product, population, and growth rate as independent variables, are used to forecast the amount of natural gas consumption for years between 2001 and 2009. Then, the forecasts are compared with real amounts of consumptions and are analyzed statistically. Consequentially, it is observed that the GA-SA hybrid algorithm made forecasts with less statistical error against linear regression. The models were used to forecast Turkey’s natural gas demand under two different scenarios for years between 2010 and 2030.

A NOTE ON “THE EFFECT OF TIME-VALUE OF MONEY ON DISCRETE TIME-VARYING DEMAND LOT-SIZING MODELS WITH LEARNING AND FORGETTING CONSIDERATIONS”

Abstract Chiu and Chen [1] considered the problem of incorporating learning, forgetting, and the time value of money into discrete time-varying demand lot-sizing models to determine lot sizes and relevant costs. They used Wagner-Whitin Algorithm (WWA) to solve the problem. But, WWA is not generating optimal solution because of the structure of learning curve used in their paper. In this paper on the other hand, a solution algorithm for the problem is introduced based on a recurrence relationship.

A hierarchical soft computing model for parameter estimation of curve fitting problems

The aim of this paper is to present an alternative solution model to estimate the coefficients of large-scaled linear and nonlinear real-life problems due to the fact that least squares and least median squares parameter estimators have some drawbacks when including so many input variables or increased size of the real-world problems. The study presents a hierarchical soft computing model (SOFTC) that consists of three stages. The first stage constitutes a real-valued breeder genetic algorithm (RVBGA). The second stage is constructing a simulated annealing (SA) algorithm in which the best parameter estimation of the RVBGA is selected as its initial point. The third stage is developing a hierarchical soft computing model by using fuzzy recombination method. SOFTC optimizes the best parameter estimations of this algorithms and it provides a trust region for parameter estimation. Three test problems, one of which is linear and others are nonlinear, are used to examine robustness of proposed models. SOFTC, RVBGA_SA and RVBGA algorithms performed the best parameter estimations, respectively, for the three test problems. The results which are discussed in detail are promising for future usage of these algorithms.Graphical abstract

GRİ STOK MODELİNİN İŞBİRLİKÇİ OYUN TEORİSİ İLE MALİYET DAĞITIMLARININ İNCELENMESİ

Stok yonetimi calismalarinda birim zamanda ortalama toplam stok maliyetini ve depolanacak urun miktarini belirlemek firmalar icin onemli bir konudur. Ancak gercek hayatta stok maliyeti parametreleri tam olarak bilinemeyebilir fakat belirli aralik olarak tahmin edilebilir. Ayrica birden fazla firma ortak hedeflere sahip olan firmalar ile stok ve siparis maliyetlerinin azaltmak icin diger firmalar ile isbirligi (koalisyon) yoluna giderek giderlerini azaltabilirler. Bu calisma ile ayni sektorde faaliyet gosteren ve ayni urunleri siparis veren firmalarin bir araya gelerek ortak siparis verme durumunda olusacak toplam maliyetin firmalar arasinda nasil dagitilacagi konularina katki saglanmistir. Uygulama gelistirmek amaciyla av silahi sektorunde faaliyet gosteren ve ayni urunleri siparis eden uc firma incelenmistir. Ayrica gelistirilen uc adet maliyet dagitim kurali olan gri orantili kural, gri esit kayip dagitim kurali, gri kacirilan alternatif kayiplarin dagitimi ile ilgili adil ve kararli dagitimlar karsilastirilarak incelenmis firmalar icin en uygun dagitim kurallari onerilmistir.

Determination Of Improvement Priorities In Education With Importance-Satisfaction Analysis And Taguchi Method: A Case Study

Eğitim hizmetlerinde müşteri ihtiyaçlarını belirlemek ve memnuniyetini sağlamak oldukça önemli ve vazgeçilmez konulardır. Bu amaçlara ulaşmak için memnuniyetsizliğe neden olan faktörlerin belirlenmesi ve gerekli düzenlemelerin yapılmasına ihtiyaç vardır. Bu çalışmada, eğitim sektöründe kalite faktörlerinin doğru olarak seçilmesi ve iyileştirilme önceliklerinin belirlenmesi amaçlanmıştır. Eğitimde hizmet kalitesini ölçmek amacıyla önem-memnuniyet modeli kullanılarak, kaliteyi etkileyen iyileştirme yapılacak faktörleri tespit etmek ve sıralamada öncelikli olanları belirlemek için Taguchi’nin istatistiksel deney tasarımı yönteminden yararlanılmıştır. Süleyman Demirel Üniversitesi Endüstri Mühendisliği Bölümü’nde öğrenim gören 26 öğrenciye öncelikle eğitim hizmetlerinden aldıkları memnuniyeti değerlendiren bir anket uygulanmış, daha sonra önceki ankette sorulan eğitimde hizmet kalitesi faktörlerine verdikleri önem derecelerini değerlendirmeleri istenmiştir. Önem-Memnuniyet modeli ile iyileştirme yapılacak faktörler belirlendikten sonra Taguchi yöntemi ile bu faktörler ankette olsun veya olmasın şeklinde 12 öğrenciye ikinci tip bir anket daha yapılarak memnuniyet dereceleri belirlenmiş ve acil iyileştirme yapılacak 4 kritik faktör belirlenmiştir. Determining customer needs and ensuring customer satisfaction are very important and essential issues in educational services. The factors which cause this dissatisfaction must be determined and the necessary arrangements must be constructed to achieve these goals. In this study, the correct selection of quality factors and determination of priorities for improvement are aimed in the education sector. Taguchi’s statistical experimental design method is used to identify and rank the factors affecting the quality to be improved by using importancesatisfaction model to measure the quality of educational services. First, a questionnaire assessing satisfaction of the education services is applied to 26 students studying in the Department of Industrial Engineering at Süleyman Demirel University and then it is asked them to evaluate the degree of education for the crucial importance of service quality factors which are asked in the earlier survey. After determining the factors to be improved by using the importancesatisfaction model, 4 critical factors to be urgently improved are determined with the Taguchi method by using a second survey asking to 12 students whether or not these factors be in the survey.

A Simulation Based Research of Alternative Organizational Structures in Sewing Unit of A Textile Factory

In textile industry, productivity, flexibility, and quality must be improved and maintained to meet the challenges of an increasingly competitive word market. Simulation has been widely used in the investigation and evaluation of organizational structures and alternatives. In textile industry, meeting the demands of customers or market changes, to make cutting right and standard, to have cutting time short and perfect, the use of new technologies and transformation into progressing organizational structures get importance for productivity. The processing time of right cutting directly affects the cycle time of the end product. In this study, the research of current organizational structure and the use of alternative organizational structures on meeting customer demands on cutting unit of a textile company are made by using ARENA® Simulation Software. Selecting the most productive organizational structure by simulation based approach to evaluate parameters is the purpose of this study and the results are evaluated.