Toy, Ayhan Özgür

Profile Picture
Profile URL
https://gcris.yasar.edu.tr/handle/123456789/12619
Name Variants
Ayhan Özgür TOY
Ayhan Özgür Toy
Job Title
Prof.Dr.
Email Address
Main Affiliation
01.01.09.03. Endüstri Mühendisliği Bölümü
Status
Current Staff
Website
ORCID ID
0000-0003-1603-6860
Scopus Author ID
14521673500
Turkish CoHE Profile ID
Google Scholar ID
GhGPH0UAAAAJ
WoS Researcher ID
F-2155-2017
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ayhan.ozgur.toy.jpg (9.27 KB)

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
1
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
1
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents

23

Citations

86

h-index

5

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Documents

19

Citations

69

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Scholarly Output

27

Articles

7

Views / Downloads

0/3

Supervised MSc Theses

5

Supervised PhD Theses

0

WoS Citation Count

19

Scopus Citation Count

29

Patents

0

Projects

0

WoS Citations per Publication

0.70

Scopus Citations per Publication

1.07

Open Access Source

3

Supervised Theses

5

JournalCount
International Conference on Intelligent and Fuzzy Systems INFUS 20225
22nd International Symposium for Production Research ISPR 20222
Pamukkale University Journal of Engineering Sciences2
4th International Conference on Intelligent and Fuzzy Systems (INFUS)2
IISE Transactions1
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Now showing 1 - 10 of 27
  • Thumbnail Image
    Conference Object
    A Comparative Study of Artificial Intelligence Based Methods for Abnormal Pattern Identification in SPC
    (SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Umut Avci; Onder Bulut; Ayhan Ozgur Toy; Toy, Ayhan Ozgur; Bulut, Onder; Avci, Umut; C Kahraman; AC Tolga; SC Onar; S Cebi; B Oztaysi; IU Sari
    Statistical process control techniques have been used to detect any assignable cause that may result in a lower quality. Among these techniques is the identification of any abnormal patterns that may indicate the presence of an assignable cause. These abnormal patterns may be in the form of steady movement in one direction i.e. trends, an instantaneous change in the process mean i.e. sudden shift, a series of high observations followed by a series of low observations i.e. cycles. As long as we can classify the observed data the decision maker can decide on actions to be performed to ensure quality standards and planning for interventions. In identification of these abnormal patterns rather than relying on human element intelligent tools have been proposed in the literature. We attempt to provide a comparative study of various classification algorithms used for pattern identification in statistical process control. We specifically consider six different types of patterns to classify. These different types are: (1) Normal (2) Upward trend (3) Downward trend (4) Upward shift (5) Downward shift (6) Cyclic. A recent trend in classification is to use deep neural networks (DNNs). However due to the design complexity of DNNs alternative classification methods should also be considered. Our focus on this study is to compare traditional classification methods to a recent DNN solution in the literature in terms of their efficiencies. Our numerical study indicates that basic classification algorithms perform relatively well in addition to their structural advantages.
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    Conference Object
    Quantitative Methods for Agri-Food Supply Chain Resilience: A Systematic Literature Review Using Text Mining
    (Elsevier, 2025) Çali, Sedef; Toy, Ayhan Özgür; Ekren, Banu Yetkin
    Agri-food Supply Chains (AFSCs) face increasing disruptions from natural disasters, pandemics, and economic crises, necessitating robust quantitative analysis for resilience. This study conducts a Systematic Literature Review (SLR) using text mining and Latent Dirichlet Allocation (LDA) to identify six key research themes, including risk management, pandemic effects, simulation-based resilience, climate change, market price volatility, and optimization models. Findings reveal that multi-criteria decision-making, simulation, optimization, and machine learning are widely used, yet gaps remain in Artificial Intelligence (AI)-driven risk prediction, real-time data integration, and adaptive decision-making This review offers insights for researchers and practitioners, emphasizing the need for AI, digital twins, and blockchain to enhance AFSC resilience. Copyright (C) 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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    Master Thesis
    Elektrikli araçların sürdürülebilirlik açısından benimsenmesinin analizi
    (2025) Şenocak, Gökcem Mısra; Öztürkoğlu, Yücel; Toy, Ayhan Özgür
    Ulaşım küresel kalkınmanın en temel unsurlarından biri olup,insanları birbirine bağlayan ve yerel ile küresel pazarlar arasında köprü kuran bir yapıya sahiptir. Tüm bu olumlu özelliklerine rağmen, çevreye en fazla zarar veren unsurlardan biri olarak da öne çıkmaktadır. Bu nedenle, ulaşımda sürdürülebilir yaklaşımların benimsenmesi büyük önem taşımaktadır. Elektrikli araçların yaygınlaşması, sürdürülebilirlik açısından kritik bir rol oynamaktadır. Literatür taramasında elektrikli araçların yaygın olarak benimsenmesini etkileyen çeşitli ekonomik, çevresel ve sosyal faktörler tespit edilmiştir. Bu çalışma, elektrikli araçların benimsenmesini sürdürülebilirlik perspektifinden değerlendirmek için Best Worst Method kullanarak temel kriterleri belirlemektedir. Ekonomik faktörlerin, yüksek başlangıç maliyetleri ve batarya maliyetlerinin, elektrikli araçların benimsenmesinde en önemli engeller olduğunu göstermektedir. Çevresel faktörler arasında ise batarya üretiminin ekolojik etkileri ve elektrikli araçların yaşam döngüsü boyunca ortaya çıkan çevresel etkiler önemli zorluklar oluşturmaktadır. Bunun yanı sıra, elektrikli araçlar hakkında bilgi eksikliği, düşük model çeşitliliği gibi sosyal faktörler de elektrikli araçlara geçişi engellemektedir. Çalışma, elektrikli araçların benimsenmesini hızlandırmak için ekonomik engellerin azaltılması, sürdürülebilir üretim uygulamalarının geliştirilmesi ve tüketici farkındalığını arttırmaya yönelik stratejilerin uygulanması gerektiğini vurgulamaktadır.
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    Article
    Hizmet lojistiğinde iş atama ve rotalama politikaları tasarımı
    (2019) Ayhan Özgür TOY; Zehra DÜZGİT; Simge ÇOBAN; Zeynep ALİBAŞOĞLU; Özlem TOK ÖZKESKİN; Mert KARAKAYA; Yücel BAYRAK
    Bu çalışmada ev aletleri endüstrisinde satış sonrası teknik servisin verimliliğini arttırmayı ele almaktayız. Verimlilik ölçütü müşteri taleplerini karşılamak üzere harcanan toplam süredir. Böylece amaç satış sonrası teknik hizmetlerinde harcanan toplam çalışma saatinin en küçüklenmesidir. Öncelikle işlerin tamamlanmasındaki gecikmenin nedenlerini belirtmek üzere sistemi analiz ettik. Analiz bulgularımız neticesinde verimliliği arttırmak üzere iş atama ve iş sıralamaya odaklanmayı seçtik. Teknisyenleri işlere atayan ve her teknisyen için bir günde harcanan toplam zamanı en aza indirgeyecek şekilde rota belirleyen karışık bir tamsayı programlama modeli önerilmiştir. Bu model ile iş sürelerinin beklenen değeri için problemi çözmekteyiz. Önerdiğimiz çözüm yöntemini gösterecek bir sayısal çalışma da sunmaktayız.
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    Conference Object
    The Facility Location Problem with Fuzzy Parameters
    (Springer Science and Business Media Deutschland GmbH, 2022) Gamze Erdem; Ayhan Özgür Toy; Adalet Oner; Toy, A. Özgür; Öner, Adalet; Erdem, Gamze; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
    There is a variety of studies about Facility Location Problems (FLP) in Operations Research (OR) literature. The studies in the literature generally assume a deterministic environment. However studies relaxing the deterministic assumption are not rare. One way of incorporating uncertainties in these problems is through fuzzy parameters. While incorporating uncertainties into the problem Fuzzy set theory has some advantages over the other popular approach to handle uncertainties which is probabilistic theory. Unlike probabilistic theory the fuzzy set theory yields a logical manner to model uncertainties without the need for any historical data. Our focus in this work is to survey the collection of the recent publications on FLP with fuzzy parameters. Uncertain demands variable costs and travel durations as well as some subjective factors that are scaled in linguistic values can be given as examples for fuzzy parameters. As a methodology of this work firstly we start by listing parameters of the classical FLP and then present studies which consider these parameters as fuzzy sets and classify them accordingly. Secondly we group these studies based on the solution methodology implemented. Our search domain for the literature is primarily the Web of Science database. However we do not limit ourselves to that database in general. Our contribution is to provide knowledge about the properties of the fuzzy environments in facility location models. © 2022 Elsevier B.V. All rights reserved.
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    Article
    Citation - WoS: 2
    Citation - Scopus: 3
    A serial inventory system with lead-time-dependent backordering: A reduced-state approximation
    (Taylor and Francis Ltd., 2023) Emre Berk; Ayhan Özgür Toy; Toy, Ayhan Ozgur; Berk, Emre
    We study a serial inventory system where the external customers may have a maximum time that they would be willing to wait for delivery in cases of stock-out and the demand would be lost if the remaining delivery lead time of the next available item is longer. This lead-time-dependent backordering behavior subsumes the models of partial backordering regardless of the wait that a customer would experience. In the inventory literature this behavior has only been analyzed in single-location settings. We study this behavior in a multi-stage setting. We consider continuous review (Formula presented.) policies at all stages facing external Poisson demands. Using the method of supplementary variables we define the stochastic process representing the inventory system and obtain the expressions for the operating characteristics of the inventory system. Based on the solution structures for the special cases we propose an approximate solution which rests on replacing the state-dependent purchasing decision of the customer with an averaged-out purchase probability computed using only the age of the oldest item. An extensive numerical study indicates that the proposed approximation performs very well. Our numerical study provides additional insights about the sensitivity and allocation of stock levels across stages. © 2022 Elsevier B.V. All rights reserved.
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    Master Thesis
    Paralel makine çizelgeleme: Konfeksiyon endüstrisinde bir uygulama
    (2023) Çini, Gülce; Toy, Ayhan Özgür; Bulut, Önder
    Bu çalışmada, giyim endüstrisine ait bir firmanın dikim aşaması incelenmiş olup, çizelgeleme problemi terminolojisi kullanılarak altı farklı tam sayılı çizelgeleme problemi formülasyonu sunulmuştur. Makinelerin aynı hız ve özelliklere sahip olması nedeniyle, sistemin özdeş paralel makine çizelgeleme problemine uygun olduğu tespit edilmiştir. İlk model, basit bir maksimum tamamlanma süresi (makespan) minimizasyonu olarak verilmiştir. Ardından, sıraya bağlı kurulum süreleri, işe hazır olma tarihleri, makine uygunluğu ve iş bölme gibi kısıtlamalar eklenerek problem genişletilmiştir. Probleme, işlerin teslim tarihleri de eklenerek amaç fonksiyonu toplam erken ve gecikmelerin minimizasyonu olarak belirlenmiştir. Geliştirilen son model bir genetik algoritma ile birleştirilmiştir. Ancak, gerçek hayattaki problemlerde, operatör öğrenme eğrisi, yorgunluğu ve makine bakım gereksinimleri gibi faktörler nedeniyle bir işin işlem süresi değişkenlik gösterebilmektedir. Aynı şekilde kurulum süreleri de insan ve teknik faktörlere bağlı olarak değişebilmektedir. Bu faktörler nedeniyle problem bulanık işlem süreleri ve bulanık kurulum süreleri ile problemin bir uzantısı olarak verilmiştir. Bu yaklaşım, bir rastgele arama algoritması, bir Monte Carlo simulasyonu, aracılığıyla karşılaştırılmıştır. Geliştirilen modeller OPL Cplex ile doğrulandıktan sonra çeşitli veriler yardımı ile optimum çözümün sonuçları ve algoritmaların çözüm sonuçları karşılaştırılmıştır ve önerilen metodolojilerin çözüm kaliteleri sunulmuştur.
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    Conference Object
    Production Planning at a Chocolate Company: A Two-Phase Approach by Aggregation
    (Springer Science and Business Media Deutschland GmbH, 2020) Zehra Düzgit; Ayşe Beyza Kuzuoğlu; Hazal Kalelioğlu; Hazal Kolay; Merve Başak Güler; Senem Akyol; Ayhan Özgür Toy; Kalelioğlu, Hazal; Kolay, Hazal; Güler, Merve Başak; Kuzuoğlu, Ayşe Beyza; Akyol, Senem; Toy, Ayhan Özgür; Düzgit, Zehra; M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , N.M. Durakbasa , M.G. Gençyilmaz
    There are some factors to be considered while developing production planning policy of chocolate and chocolate-based products. One of these factors is that chocolate is a perishable food therefore it has limited shelf life. Another factor is that, its demand is not always easy to forecast. Holidays mothers’ day teachers’ day valentines’ day and new year are examples of the peak periods. For these special days demand generally follows a seasonal demand pattern where seasonality may also contain trend for some specific product types. Moreover there are two religious holidays (Ramadan Feast and Feast of Sacrifice) in Turkey whose dates shift each year. This phenomenon makes forecasts challenging. Underestimating demand causes loss of customer goodwill lost customers and market share whereas overestimating demand causes excess inventory to keep in stock and risk of fat blooming. Accurate forecasting is critical since it provides a fundamental input for the production plan. The study is conducted in a chocolate company in Turkey. The company does not implement a systematic planning method for chocolate production instead the planning is based on past experiences with respect to experts’ opinions. The objective of this study is to determine the optimal production and ending inventory levels for the period of 2018 so as to minimize total production and inventory holding cost subject to production inventory and capacity related restrictions. A two-phase optimization method is adopted as a solution method. Firstly a mathematical model is developed for the monthly aggregate production planning on product group basis. In order to solve the problem monthly demand for product groups are forecasted based on the sales data of the previous two years. Secondly a mathematical model for weekly disaggregate production planning is developed for each end item using the outputs of the aggregate planning as input. The disaggregate production plan gives the weekly planned production and inventory levels for end items for year 2018 with minimum deviation from the aggregate plan. Although the proposed solution model is implemented for year 2018 it can be used for the coming years by updating some parameters. © 2022 Elsevier B.V. All rights reserved.
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    Conference Object
    Citation - Scopus: 2
    Intelligent Supply Chains Through Implementation of Digital Twins
    (Springer Science and Business Media Deutschland GmbH, 2022) Oray Kulaç; Banu Yetkin Yetkin Ekren; Ayhan Özgür Toy; Toy, A. Ozgur; Kulac, Oray; Ekren, Banu Y.; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
    Data-driven decision-making process can be defined to be the sequential activities of real-time data collection data analytics optimization and decision making. Developments in Industry 4.0 technologies have made it possible to realize that new quality decision-making process. When that decision-making process is performed under the simulation model of a system developed on real-time data-based and end-to-end connection manner to prevent the disruption risks and to improve resilience in a system then it constitutes a digital twin (DT). A DT is a virtual representation of an object or system that can help organizations monitor operations perform predictive analytics and improve processes. For instance a DT could provide a digital replica of the operations of a factory communications network or the flow of goods through a supply chain system. In this work we focus on DT implementations in supply chain networks. We present state of the art implementation of DTs in supply chains and their prospective utilizations towards creating intelligent supply chains. © 2022 Elsevier B.V. All rights reserved.
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    Conference Object
    Citation - Scopus: 1
    An Implementation of Flexible Job Shop Scheduling Problem in a Metal Processing Company
    (Springer Science and Business Media Deutschland GmbH, 2021) Ali Ozan Özkul; Gamze Küçük; Ceren Çelik; Nevzatcem Öztuna; Mert Demirkan; Ezgi Çağlar Nizam; Yıldırımşan Büyükmertoğlu; Damla Yüksel; Ayhan Özgür Toy; Nizam, Ezgi Çağlar; Demirkan, Mert; Küçük, Gamze; Öztuna, Nevzatcem; Özkul, Ali Ozan; Toy, Ayhan Özgür; Çelik, Ceren; N.M. Durakbasa , M.G. Gençyılmaz
    In this study we consider the flexible job-shop scheduling problem at a local metal sheet processing company. We aim to develop a model and an algorithm to generate a weekly production plan for the company. The objective is to minimize the makespan while meeting the demands of products for a given planning horizon. First we provide an LP formulation of this problem. The computational complexity of the problem is NP-hard hence the input data prohibits obtaining the optimal solution in a reasonable time. Therefore we implement a metaheuristic and several rule-based heuristics. These are Genetic Algorithm Giffler and Thompson’s Algorithm and three other Rule-Based Heuristic Algorithms that we developed. We first test our model and heuristics over a set of sample instances then we solve for the real data. Our experimental study indicates that one of the rule-based heuristics we developed outperforms others in most of the instances. © 2020 Elsevier B.V. All rights reserved.