Download
Teaching Warehousing Concepts through Interactive Animations and 3-D Models

Dr. Gürdal Ertek recommends the following related books:

Facility Logistics: Approaches and Solutions to Next Generation Challenges (Resource Management) 1st Edition

World-Class Warehousing and Material Handling 1st Edition

Order picking is typically the most costly operation in a warehouse and traveling is typically the most time consuming task within order picking. In this study we focus on the layout design for a rectangular warehouse, a warehouse with parallel storage blocks with main aisles separating them. We specifically analyze the impact of adding cross aisles that cut storage blocks perpendicularly, which can reduce travel times during order picking by introducing flexibility in going from one main aisle to the next. We consider two types of cross aisles, those that are equally spaced (Case 1) and those that are unequally spaced, which respectively have equal and unequal distances among them. For Case 2, we extend an earlier model and present a heuristic algorithm for finding the best distances among cross aisles. We carry out extensive computational experiments for a variety of warehouse designs. Our findings suggest that warehouse planners can obtain great travel time savings through establishing equally spaced cross aisles, but little additional savings in unequally-spaced cross isles. We present a look-up table that provides the best number of equally spaced cross aisles when the number of cross aisles (N) and the length of the warehouse (T) are given. Finally, when the values of N and T are not known, we suggest establishing three cross aisles in a warehouse.

Ertek, G., Incel, B. and Arslan, M. C. (2007). “Impact of Crossaisles in a rectangular warehouse: A computational study,” in Facility Logistics: Approaches and Solutions to Next Generation Challenges, Editor: Maher Lahmar. Auerbach.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

Download
Teaching Warehousing Concepts through Interactive Animations and 3-D Models

Dr. Gürdal Ertek recommends the following related books:

Facility Logistics: Approaches and Solutions to Next Generation Challenges (Resource Management) 1st Edition

World-Class Warehousing and Material Handling 1st Edition

In this paper we present a study where we visually analyzed science citation data to investigate the competitiveness of world countries in selected categories of science. The data set that we worked on in our study includes the number of papers published and the number of citations made in the ESI (Essential Science Indicators) database in 2004. The data set lists these values for practically every country in the world. In analyzing the data, we employ methods and software tools developed and used in the data mining and information visualization fields of the Computer Science. Some of the questions for which we look for answers in this study are the following: (a) Which countries are most competitive in the selected categories of science? (i.e. Engineering, Computer Science, Economics & Business) (b) What type of correlations exist between different categories of science? For example, do countries with many published papers in the field of Engineering science also have many papers published on Computer Science or Economics & Business? (c) Which countries produce the most influential papers? This analysis is needed since a country may have many papers published but these papers may be cited very rarely. (d) Can we gain useful and actionable insights by combining science citation data with socioeconomic and geographical data?

Arslan, M. C. and Ertek, G. (2007). “Visual mining of science citation data for benchmarking scientific and technological competitiveness of world countries.” 2. International Conference on Technology and Economic Development, Izmir, Turkey.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

Download
Visual Mining of Science Citation Data for Benchmarking Scientific and Technological Competitiveness of World Countries

Dr. Gürdal Ertek recommends the following related books:

Information Visualization: Design for Interaction (2nd Edition)

We present a data mining framework that can be applied for analyzing patient arrivals into healthcare centers. The sequentially applied methods are association mining, text cloud analysis, Pareto analysis, cross-tabular analysis, and regression analysis. We applied our framework using real-world data from a one of the largest public hospitals in the U.A.E., demonstrating its applicability and possible benefits. The dataset used was eventually 110,608 rows in total for the regression models, covering the most utilized 14 hospital units. The dataset is at least 10-fold larger than datasets used in closely-related research. The developed data mining framework can provide the input for a subsequent optimization model, which can be used to optimally assign appointments for patients, based on their arrival patterns.

Abdallah, S., Malik, M., Ertek, G. (2017) A Data Mining Framework for the Analysis of Patient Arrivals into Healthcare Centers. ICIT 2017 Proceedings of the 2017 International Conference on Information Technology. Pages 52-61. Singapore. December 27 – 29, 2017. ACM.

The published paper can be accessed from the following URL:

https://dl.acm.org/citation.cfm?id=3176740

The presentation for this paper received the Best Presentation Award from among 11 presentations in its session at ICIT 2017.

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics

Information Visualization: An Introduction by Robert Spence (2014-11-04) 

Download this paper.

While the global production of wind energy is increasing, there exists a significant gap in the academic and practice literature regarding the analysis of wind turbine accidents. Our paper presents the results obtained from the analysis of 240 wind turbine accidents from around the world. The main focus of our paper is revealing the associations between several factors and deaths & injuries in wind turbine accidents. Specifically, the associations of death and injuries with the stage of the wind turbine’s life cycle (transportation, construction, operation, and maintenance) and the main cause factor categories (human, system/equipment, and nature) were investigated. To this end, we conducted a detailed investigation that integrates exploratory and statistical data analysis methods with data mining methods. The paper presents a multitude of insights regarding the accidents and discusses implications for wind turbine manufacturers, engineering and insurance companies, and government organizations.

Please cite this paper as follows:

Asian, S., Ertek, G., Haksoz, C., Pakter, S. and Ulun, S., 2017. Wind turbine accidents: A data mining study. IEEE Systems Journal, 11(3), pp.1567-1578.

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics

Information Visualization: An Introduction by Robert Spence (2014-11-04) 

Wind Energy Explained: Theory, Design and Application

Data collected and generated through and posterior to projects, such as data residing in project management software and post-project review documents, can be a major source of actionable insights and competitive advantage. This paper presents a rigorous methodological analysis of the applied research published in academic literature, on the application of data mining (DM) for project management (PM). The objective of the paper is to provide a comprehensive analysis and discussion of where and how data mining is applied for project management data and to provide practical insights for future research in the field.

Ertek, G., Tunc, M.M., Zhang, A.N., Tanrikulu, O., Asian, S. (2017) Data Mining of Project Management Data: An Analysis of Applied Research Studies. ICIT 2017 Proceedings of the 2017 International Conference on Information Technology. Pages 35-41. Singapore. December 27 – 29, 2017. ACM.

The published paper can be accessed from the following url:
https://dl.acm.org/citation.cfm?id=3176714

Download the paper & the presentation.

Dr. Gürdal Ertek recommends the following related books:

Essentials of Business Analytics

Rapid Miner

Download the final draft of this paper.

Today’s highly competitive business world requires that managers be able to make fast and accurate strategic decisions, as well as learn to adapt to new strategic challenges. This necessity calls for a deep experience and a dynamic understanding of strategic management. The trait of dynamic understanding is mainly the skill of generating additional knowledge and innovative solutions under the new environmental conditions. Building on the concepts of information processing, this paper aims to support managers in constructing new strategic management knowledge, through representing and mining existing knowledge through graph visualization. To this end, a three-stage framework is proposed and described. The framework can enable managers to develop a deeper understanding of the strategic management domain, and expand on existing knowledge through visual analysis. The model further supports a case study that involves unstructured knowledge of profit patterns and the related strategies to succeed using these patterns. The applicability of the framework is shown in the case study, where the unstructured knowledge in a strategic management book is first represented as a semantic network, and then visually mined for revealing new knowledge.

Ertek, G., Tokdemir, G., Sevinç, M., & Tunç, M. M. (2017). New knowledge in strategic management through visually mining semantic networks. Information Systems Frontiers, 19(1), 165-185.

Download:
New Knowledge in Strategic Management through Visually Mining Semantic Networks

Dr. Gürdal Ertek recommends the following related books:

Information Visualization: An Introduction by Robert Spence (2014-11-04) 

Strategic Management: Concepts 3rd Edition