Üretim sistemleri örneklerinde belirsiz/dinamik optimizasyon problemlerinin modellenmesi ve çözümü

In most of the optimization problems, the problem related data as well the problem domain is assumed to be exactly known beforehand and to remain stationary throughout optimization process. However, majority of real-life problems are dynamic in their nature due to unpredictable events. Such problems with time-varying problem domain or with changing parameters are referred as dynamic optimization problems in the related literature. The aim here is not only to find the global optimum of a single problem environment, but also to track the moving optima. The importance of dynamic optimization for manufacturing systems has been stressed by many authors particularly in the last decade. However, most of the published work includes only synthetic and theoretical problems commonly used as benchmarks. Practical implementations of dynamic optimization concepts in real-life manufacturing systems are lacking. Therefore, this thesis fills a gap by focusing on implementations of these concepts on a variety of real-life manufacturing applications. In this respect, first, a variety of approaches is developed and is tested on the well-known benchmarks including both continuous and combinatorial dynamic problems. Next, some of these approaches are tested on real-life manufacturing systems applications through funded scientific projects. Besides the practicability and simplicity in adaptation of these approaches to real-life systems, it is also shown that, satisfactory results can be achieved by these methods.