Bread waste is a significant economic and environmental problem for many countries. In this paper, we propose a system dynamics approach for bread waste problem that involves significant complexities such as feedbacks and dynamic elements. System dynamics modelling is a simulation method that allows to model these complexities and investigate the impact of public policies on the system performance. We develop a system dynamics model of bread production and consumption dynamics within a geographical area. We design numerous computational experiments by using the related data from Istanbul, Turkey. The experiments suggest that the shelf life is the most important factor on the waste production: doubling the shelf life of the bread can reduce the bread waste by 25%. Ekmek israfı pek çok ülke için önemli bir mali ve çevresel sorun oluşturmaktadır. Bu problem, içinde pek çok geri besleme döngüsü içeren, dinamik ve karmaşık bir sistem problemidir. Bu çalışmada, ekmek israfının oluşumu sistem dinamiği yöntemiyle analiz edilmiştir. Sistem dinamiği yöntemi geri besleme döngüleri içeren dinamik problemlerin modellenmesine ve analiz edilmesine olanak sağlayan bir yaklaşımdır. Bu çalışmada sunulan model, ekmek üretim ve tedarik zincirinin çesitli aşamalarını kapsamaktadır. Oluşturulan model farklı parametre değerleri ve gelecek senaryoları altında test edilmiş, sonuçlar analiz edilmiştir. Simulasyon senaryolarında İstanbul şehrine ait veri seti kullanılmıştır. Senaryo sonuçları ekmek israfının önlenmesinde en önemli faktörün ekmeğin raf ömrü olduğunu göstermiştir. Ekmeğin raf ömrünün iki katına çıkarılmasının ekmek israfını %25 oranında azaltabileceği bulunmuştur.
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Stem‐cell transplantation is the last chance for patients of various blood‐related diseases. Stem‐cell donation centers admit patients in need of a stem‐cell transplant and search for a perfect match between the patients and donors. The search process is time‐consuming and requires expensive advanced equipments, in particular for DNA typing. In this study, we are concerned with a capacity planning problem in a network of stem‐cell donation centers. The underlying optimization model integrates the operations for a donor search and aims to maximize the number of transplantations. A scenario‐based stochastic programming approach is introduced to investigate the effect of the demand and service time variabilities into the capacity planning problem. We consider the maximum possible waiting time during the search process to obtain robust solutions against uncertainties. For this purpose, we approximate the maximum waiting time in the advanced blood testing with a robust queuing approach. The computational experiments are designed to illustrate the performance of the capacity planning model.
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