Zeynep D. U. Durmusoglu

A Hybrid MCDM for Private Primary School Assessment Using DEMATEL Based on ANP and Fuzzy Cognitive Map

AbstractPrimary school selection is actually a decision making problem that should be supported with several source of information. Parents usually handle this problem in an unstructured manner which is indeed a fuzzy mental ranking of schools with respect to the effectiveness. In this study, an analytical hybrid multiple criteria decision making (MCDM) model is proposed and explained with details for private primary school selection problem. A case study indicating primary school choices of parents in Turkey is also presented.

An Analysis of Trends in Publications on "Tobacco Control".

Objectives: Publications on tobacco control were quantitatively analysed to gain insight into the essential characteristics of the research field and trends and patterns in publication activities. The goal was to detect changes in the number of publications before and after the World Health Organization Framework Convention on Tobacco Control (WHO FCTC) was introduced. Study design: A bibliometric analysis was performed to assess the current status and research themes of tobacco control papers listed in the Web of Science database published between 1990 and 2015. Methods: Quantitative analyses were conducted to investigate publication activities, geographic distribution and individuals’ research fields within tobacco control. Results: The number of publications on tobacco control was over 81 times higher in 2015 than in 1990. At least 50% of the papers were published by authors in high-income countries. In addition, in the first 5 years after the WHO FCTC was introduced, publications on tobacco control increased considerably and the first publications from authors from Malaysia and Uruguay appeared. Researchers from the Americas Region of WHO contributed to the field much more frequently than those from the other five WHO regions. Conclusion: Findings from this study suggest that researchers’ interest from most countries increased after the WHO FCTC was introduced. However, research outputs from low- and middle-income countries remained comparatively low. Promoting more interest in tobacco control among researchers in these countries may help control the future prevalence of smoking.Objectives:Publications on tobacco control were quantitatively analysed to gain insight into the essential characteristics of the research field and trends and patterns in publication activities. T...

A classification scheme for agent based approaches to dynamic optimization

Several papers in the literature employ agent-based modeling approach for providing reasonable solutions to dynamic optimization problems (DOPs). However, these studies employ a variety of agent-based modeling approaches with different strategies and features for different DOPs. On the other hand, there is an absence in the literature of a formal representation of the existing agent-based solution strategies. This paper proposes a representation scheme indicating how the solution strategies with agent-based approach can be summarized in a concise manner. We present these in a tabular form called “Agent Based Dynamic Optimization Problem Solution Strategy” (ABDOPSS). ABDOPSS distinguishes different classes of agent based algorithms (via communication type, cooperation type, dynamism domain and etc.) by specifying the fundamental ingredients of each of these approaches with respect to problem domain (problems with dynamic objective functions, constraints and etc.). This paper also analyzes 18 generic studies in the literature employing agent-based modeling based on ABDOPSS.

Using Google trends data to assess public understanding on the environmental risks

ABSTRACT This study proposes a method to assess the public understanding toward themes related to environment, biodiversity conservation and fishery. Since the Internet traffic is seen as the proxy of the public interest, this article analyzes the related Google Trends data to explore the cognitive map of the public. Patterning changes in the search volume (synchronous increase and decrease) were detected by using the association analysis. Weekly search volumes of the United States for the last 5 years have been gathered and were converted into values ranging between –1 and 1, indicating the gradual level of increase/decrease by the time. Apriori algorithm was used to determine the associations between search volumes of the keywords. As a consequence, several patterns were detected with a significant support indicating synchronous increases/decreases of the volumes. Upon the development of cognitive maps based on the detected patterns, it is found that the terms “Environment” and “Pollution” were the most significant and central terms. The search volume of the terms such as “Conservation,” “Ecology,” “Climate change,” “Invasive species” and “Endangered Species” increases as the search increases in the central terms. Therefore, these terms can be seen as the drivers/triggers of the Google search for some central words. It is apparent that the public has awareness of the central terms and further interest should be provoked and fostered on the environment-related concepts.

A multi-agent based approach to modeling and solving dynamic generalized travelling salesman problem

This paper introduces four different types of Generalized Travelling Salesman Problem (GTSP) which are actually dynamic variants of the well-known logistics problems. For all of these defined types, new cities are added to/deleted from the city domain during the travelling of the salesman. This city addition and deletion during the solution phase of the problem, differentiates the proposed types from the classical GTSP. Since these variants of GTSP are relatively complicated compared to classical forms, an agent-based strategy is proposed in this paper to handle complexity and dynamism. In this respect, proposed agent-based strategy employs a general manager and numerous region agents to control and coordinate the dynamism in their regions and in the central level. Region agents create solutions just for their regions and thereby complexity of obtaining a central solution for each change containing is avoided. Findings of the proposed agent-based strategy confirm that adaptation ability of agent-based strategy against the dynamism is significantly better than classical central solution approach. In this respect, this paper is expected to be novel in two respects. First, those four types of GTSP defined in this paper, are different from the classical GTSP since they have dynamic city domain. Second, the proposed novel agent-based solution strategy is capable to create solutions in a timely manner.

Enhancing technology clustering through heuristics by using patent counts

International Patent Classification (IPC) system is a hierarchical classification structure used essentially to classify and explore patents along with the technical fields which they are concerned with. Therefore, corresponding number of patents for a certain IPC, can serve as an indicator of technical developments in the relevant area. These numbers can also form a basis for investigating state of the art for a particular field of technology. This paper proposes an approach for clustering of patents for those of the technologies listed by IPC via the number of patent counts. A set of n real numbers indicating the patent counts for different technologies is partitioned into k clusters such that the sum of the squared deviations from the mean-value within each cluster is minimized. With this purpose in mind, two different heuristics have been considered for clustering since complete enumeration would take considerable solution time. The first heuristic is specifically proposed for this study and the second one is Great Deluge Algorithm (GDA) which has been extensively used for solving complicated problems. The proposed heuristics are coded in visual basic (VB) 6.0 and a user interface is developed for the program. The developed program attempts to find the appropriate k value in order to make the best possible clustering. As an application of the proposed clustering approach, patent data that is retrieved from web site of Turkish Patent Institute (TPI) has been used for clustering technologies.

A TOPSIS-based approach for sustainable layout design: activity relation chart evaluation

Purpose The purpose of this study is to propose an approach for assessing sustainability aspect of facility layouts. Activity relationship chart (ARC) is a widely used assistive tool for facility layout design which assesses closeness requirement among all pairs. In a typical ARC, there are six closeness ratings which may be assigned to each pair of departments. Ratings are evaluated by considering a single factor or an overall rating is provided. On the other hand, there may be more than one criterion which has to be evaluated separately and then a fair decision should be taken by considering the relative weight of factors. With this purpose in mind, ARC alternatives are evaluated on the basis of three factors which are environmental aspect, safety concerns and manufacturing efficiency factors by using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. Design/methodology/approach In this paper, more than one ARC alternatives are evaluated by considering environmental, safety and manufacturing efficiency factors. Alternatives are then ranked via TOPSIS. An empirical case study is also presented to validate how effective the proposed model performs. Findings The TOPSIS method can be successfully used to choose the most sustainable ARC alternative appropriately by the help of experts. The proposed approach can be beneficial to researchers and practitioners for better understanding the ARC evaluation problem from the perspective of sustainability. Practical implications The obtained results confirm that the proposed model can assist practitioners in refining their decision processes, particularly in cases where there are many ARC alternatives to be considered. Originality/value This is the first time that this method is used in such a context. This study contributes to literature by presenting practical applications of TOPSIS in the ARC assessment field. It should be highlighted that there is no comparable research on the evaluation of ARCs using TOPSIS. Thus, this study fills the gap by providing an analytical approach in this area.

Classification of smoking status: The case of Turkey

Smoking tobacco products has become a deadly and prevalent habit. It is a known fact that smoking negatively affects the health, economic expenditures, and social life of not only users but also second hand smokers (peoples exposure to smoke). Inhaling tobacco smoke can make people vulnerable to nicotine addiction. Correspondingly, second hand smokers may become daily or less than daily smokers in time. The main objective of the presented paper was to classify smoking status of people considering second-hand smoking associated attributes: allowance to second hand smoking at home, allowance to second hand smoking at work, exposure to smoke at work in the past 30 days, beliefs that second hand smoking causes serious diseases, and gender. The classes of smoking status were defined as daily smoker, less than daily smoker and no smoker (not at all). The classification was performed using multilayer perceptron that is a well known neural network approach. The results showed that multilayer perceptron could correctly classify the smoking status of people over % 68 using five attributes. The systems like tobacco use consist of many different interacting factors that make them more complex and dynamic to analyze (classify). For that reason, the % 68 accuracy level can be interpreted as sufficient to the analysis performed for this kind of problems.