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1.
A Comparison of Traditional and Modern Data Warehouse Architectures : zaključno delo
Rok Virant, 2021, undergraduate thesis

Abstract: Data has never been as desired or valued as it is today. The value of data and information over the past decade has not only changed trends in business and the IT industry but has also changed the dynamic of work. Enormous amounts of aggregate data offer companies and other corporations the option to explore and study data samples. Data collection and information processing are new dynamic factors, not only for individuals but also for corporations. Companies and corporations who are able to process large amounts of data in the shortest possible time can place themselves in a leading position in certain professions. In this bachelor’s thesis we will describe the basic concepts and factors that have shaped new, cloud-based data warehouse technologies. At the same time, we also emphasize why and how these technologies are used. We focus on how the changing technology influenced the users and their consumption of data, the changing dynamics of work as well as the changes of data itself. In the practical part, we created two DWH environments (on-premises and cloud) that we compare with each other. In the experiment, we underlined the fact that CDWHs are in certain situations not always faster than TDWH.
Keywords: Data Warehouses, Cloud Computing, Outsourcing, Data, Information
Published in DKUM: 18.10.2021; Views: 1009; Downloads: 168
.pdf Full text (3,58 MB)

2.
Method for evaluating the throughput performance of shuttle based storage and retrieval systems
Tone Lerher, Banu Y. Ekren, Zaki Sari, Bojan Rosi, 2016, original scientific article

Abstract: In this paper a method for throughput performance calculation of shuttle based storage and retrieval systems (SBS/RS) is presented. SBS/RS represent a new technology in automated storage and retrieval systems. Since it is important to design SBS/RS right the first time due to the relative inflexibility of the physical layout, we provide a proposed method for the throughput performance calculation of these systems. The performance of the system is considered as a throughput capacity of the SBS/RS as a whole.
Keywords: automated warehouses, performance analysis, shuttle based systems, storage, logistics
Published in DKUM: 12.07.2017; Views: 1386; Downloads: 444
.pdf Full text (611,95 KB)
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3.
Multi-objective optimization of automated storage and retrieval systems
Tone Lerher, Matjaž Šraml, Matej Borovinšek, Iztok Potrč, 2013, original scientific article

Abstract: The multi-objective optimization of automated warehouse is discussed and evaluated in present paper. Since most of researchers in material handling community had performed optimization of decision variables with single objective function only (usually named with minimum travel time, maximum throughput capacity, minimum cost, etc.), the multi-objective optimization (time-cost-quality) will be presented in present research. For the optimization of decision variables in objective functions, the method with genetic algorithms is used. The main objective of our contribution is to determine the performance of the system according to the multi-objective optimization technique.
Keywords: automated warehouses, performance, multi-objective function, optimization
Published in DKUM: 10.07.2015; Views: 1056; Downloads: 68
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4.
A multi-objective optimization approach for designing automated warehouses
Tone Lerher, Matej Borovinšek, Iztok Potrč, Matjaž Šraml, 2012, published scientific conference contribution

Abstract: A multi objective optimization of automated warehouses is discussed and evaluated in present paper. Since most of researchers in material handling community had performed optimization of decision variables with single objective function only (usually named with minimum travel time, maximum throughput capacity, minimum cost, etc.), the multi objective optimization (travel time - cost - quality) will be presented. For the optimization of decision variables in objective functions, the method with genetic algorithms is used. To find the Pareto optimal solutions, the NSGA II genetic algorithm was used. The main objective of our contribution is to determine the performance of the system according to the multi objective optimization technique. The results of the proposed model could be useful tool for the warehouse designer in the early stage of warehouse design.
Keywords: automated warehouses, material handling, multi objective optimization
Published in DKUM: 10.07.2015; Views: 1244; Downloads: 33
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