Mahir Öner - Academia.edu (original) (raw)

Papers by Mahir Öner

Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems, 2018

Supply chain management paradigms are becoming increasingly common management perspectives all ov... more Supply chain management paradigms are becoming increasingly common management perspectives all over the world due to violent global competition of trade organizations and rapid changes in technology. In recent years, thanks to the communication improvements, customers have become more conscious about purchasing goods or services. Furthermore, organizations have to be customer oriented and more flexible against the dynamism of supply chain environment which increases uncertainties in supply chain parameters. Although a considerable amount of risk factors appearing in supply chain operations, this study concentrates on detecting key supply chain risks which could cause abnormalities and occur from rapid changes in customer demand, unpredictable price fluctuations, defect variations and delivery delays and provides the correction of these problems automatically. Thus, a system dynamics model is established for determining risks. This combined approach would be helpful for integrated su...

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making, 2019

With the development of information technologies, data volumes have increased and the processing ... more With the development of information technologies, data volumes have increased and the processing of numerous data has become a necessity for handling the competition, especially for food sector. In this context, hourly online order demand was estimated from 34 restaurants in fast food sector covering the period of January 2016–September 2017 by using as Logistic regression+Adaboost algorithm, SVM+Adaboost algorithm, NARX+Adaboost algorithm, ARIMA+Adaboost algorithm and Random Forest+Adaboost algorithm in crispcollective learning models. In addition to that case, fuzzy SVM, fuzzy ANN and fuzzy logistic regression and fuzzy random forests are also applied for the further analysis of fuzzification of classification process. According to the estimation parameters (Sensitivity, Specificity and Accuracy), fuzzy random forests technique was found to provide the best predictive performance. This better results can be thought from the aggregation rule that depend on Hamming distances which a...

Data Science and Knowledge Engineering for Sensing Decision Support, 2018

Research Anthology on Cross-Industry Challenges of Industry 4.0, 2021

The new form of future generation machines and automated systems could be synchronized by IoT ada... more The new form of future generation machines and automated systems could be synchronized by IoT adaptation. By this way, a very large size data can be carefully stored in data repositories and have to be analyzed for extracting knowledge. Thus, optimization techniques are becoming invaluable tools for finding patterns from parallel distributed machines. On the other hand, statistical methods and optimization models could not be utilized efficiently due to excessive dimension of data. Additionally, data analytics should be applied and results should be gathered by using practical approaches especially for security, access control and fault detection issues. In this study, optimization techniques are evaluated in the perspective of big data analytics and both mathematical and statistical methods will be extensively analyzed for different versions of problem solving and decision making in Industry 4.0 era.

Research in Transportation Business & Management, 2019

Abstract This study aims to develop a quantitative assessment framework for public bus operators ... more Abstract This study aims to develop a quantitative assessment framework for public bus operators to translate the passenger demands into service quality specifications. The results of a customer satisfaction survey, carried out to identify the passenger demands, are used as an input to measure the level of service quality in a public transport operator. Firstly, the number of customer satisfaction criteria is reduced with Principal Component Analysis (PCA) and secondly the evaluation factors are identified with Quality Function Deployment (QFD). Both methods are integrated with an interval-valued intuitionistic fuzzy (IVIF) approach to reflect the uncertainty in the QFD evaluations of decision makers. By this way, our approach synthesizes customer and design requirements via interval-valued intuitionistic fuzzy QFD. The results show that the proposed method helps decision makers of public bus operators to focus on high priority areas so that they can effectively deploy their resources to address people's mobility needs.

Journal of Intelligent & Fuzzy Systems, 2019

The improvements in mobile technologies led to the wide adaptation and triggered the demand for l... more The improvements in mobile technologies led to the wide adaptation and triggered the demand for location based services. In this respect, examining user similarities enable the analysis of user interests in terms of the determination of purchasing preferences and actual needs. User similarities are generally extracted from consumer life style, demographical information or the reflections from previously sent messages. In spite of the fact that these factors may not directly influence the purchasing decision, uncertain or lack of information can be encountered while establishing recommendation systems. Thus, researchers try to search other indicators that can reflect customer characteristics from spatial data, digital contribution in social media and search history for preferable representation of the changes in purchasing tendency. In this study, social platform based interval valued intuitionistic fuzzy location recommendation system is proposed by considering three common social platforms: Trip Advisor, Zomato and Foursquare. To perform restaurant offers to appropriate social platform users, a sentiment analysis is conducted to selected restaurants and number of negative, positive and neutral comments are extracted. After that, restaurant and location information are examined by using user, restaurant and location clustering via fuzzy clustering. Finally, intuitionistic fuzzy similarity matrix based collaborative filtering is used for restaurant offers to similar users.

Geoderma, 2018

In this study, a novel fuzzy multi-criteria decision-making method based on hesitant fuzzy sets c... more In this study, a novel fuzzy multi-criteria decision-making method based on hesitant fuzzy sets combined with the Choquet integral (HFSCI) is proposed to prevent soil erosion in Turkey. Owing to the hierarchical structure of the problem, the main criteria accounted for in this work are the topography of the area, land usage and cover, climate effects, soil characteristics, and human activities, which are accompanied by appropriate sub-criteria. According to the soil structure and potential risk factors, four preventive methods are determined: land reforestation, agricultural terracing, windbreak construction, and the application of suitable farming techniques. The results obtained in this study demonstrated that the proposed approach enables decision makers to select the appropriate method to prevent soil erosion. Additionally, a comparison of the proposed approach and another hesitant-based approach is provided to demonstrate the validity of the recommended approach.

Journal of Intelligent & Fuzzy Systems, 2020

Since information science and communication technologies had improved significantly, data volumes... more Since information science and communication technologies had improved significantly, data volumes had expanded. As a result of that situation, advanced pre-processing and analysis of collected data became a crucial topic for extracting meaningful patterns hidden in the data. Therefore, traditional machine learning algorithms generally fail to gather satisfactory results when analyzing complex data. The main reason of this situation is the difficulty of capturing multiple characteristics of the high dimensional data. Within this scope, ensemble learning enables the integration of diversified single models to produce weak predictive results. The final combination is generally achieved by various voting schemes. On the other hand, if a large amount of single models are utilized, voting mechanism cannot be able to combine these results. At this point, Deep Learning (DL) provides the combination of the ensemble results in a considerable time. Apart from previous studies, we determine var...

Advances in Logistics, Operations, and Management Science, 2018

International Journal of RF Technologies, 2018

The value of radio frequency identification (RFID) technology is critical for the supply chain, e... more The value of radio frequency identification (RFID) technology is critical for the supply chain, especially in the wool yarn industry, due to the high levels of complicated distribution processes and logistics operations in warehouse. This paper considers a case study for the use of RFID technology in the wool yarn industry. It is aimed at the handling process, such as: tracking work-in-progress, tracking inventories, counting stock, receiving, picking, and shipping of semifinished products. To do this, an architectural framework of the RFID-based information system for the wool yarn industry was designed, and a cost-benefit analysis was performed to further evaluate whether the new system is economical or not. Also risk analysis was performed for RFID investment.

Considering high competitive nature of today's industries, being on plan is very vital for supply... more Considering high competitive nature of today's industries, being on plan is very vital for supply chain network of an organization. All the flows of materials from initial suppliers to final customers need to be smooth. Hence, distribution network design is an important strategic decision problem for the supply chain managers. The aim of this research is to propose a web-based Decision Support System (DSS) for optimizing fuzzy distribution network in the context of supply-chain management. A fuzzy goal-programming model has been designed for the proposed DSS to consider the uncertain and imprecise data. This research focuses on four conflict fuzzy goals of (i). all demands must be covered by distribution center, (ii). investment goals for opening new sites considering fix costs, (iii). Investment goals for opening new distribution centers considering fix costs, (iv). Supply costs goals, to meet the optimized results. Hence with those attributes of membership function of goals, the decision makers can apply this model to obtain the investment policy and the achieved level of each individual goal.

The International Journal of Advanced Manufacturing Technology, 2016

Since radio frequency identification technology usage is increasing, applications in this area ha... more Since radio frequency identification technology usage is increasing, applications in this area have a rising trend day by day. However, successful studies related to radio frequency identification implementation, which combine many different areas, are not sufficient enough. Studies have mostly emphasized theoretical approaches rather than being practical studies. In this study, a roadmap for radio frequency identification design, configuration and deployment is presented in order to design an integrated approach as pointed out in the literature and in former radio frequency identification projects. Additionally, an application is performed for validation and reinforcing of the understanding of the proposed radio frequency identification implementation roadmap; an architectural framework and economic feasibility are also discussed. The most striking result from the case study is that a radio frequency identification application could be successfully implemented to support the tracking and tracing of work in process in denim production processes, an area in which studies about radio frequency identification applications have not been done. Besides this, redundant inventory and production costs, redundant labour costs caused by inefficient production activities, inaccuracies of records, incorrect order deliveries and penalty costs incurred by customers are significantly reduced, which provides invaluable advantages in the real-life competition of the denim product industry.

Springer Series in Advanced Manufacturing