Fadiloğlu, Murat
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Fadıloglu, M. Murat
Fadıloglu, MM
Fadıloğlu, Mehmet Murat
Fadıloglu, Mehmet Murat
Fadiloglu, M. Murat
Fadiloglu, MM
Fadiloglu, Mehmet Murat
Fadıloğlu, Murat
Fadıloglu, MM
Fadıloğlu, Mehmet Murat
Fadıloglu, Mehmet Murat
Fadiloglu, M. Murat
Fadiloglu, MM
Fadiloglu, Mehmet Murat
Fadıloğlu, Murat
Job Title
Email Address
murat.fadiloglu@ieu.edu.tr
Main Affiliation
05.09. Industrial Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
5
GENDER EQUALITY
0
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
2
Research Products
13
CLIMATE ACTION
0
Research Products
8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
14
LIFE BELOW WATER
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
1
NO POVERTY
0
Research Products
2
ZERO HUNGER
0
Research Products
4
QUALITY EDUCATION
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
3
GOOD HEALTH AND WELL-BEING
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
10
REDUCED INEQUALITIES
0
Research Products
15
LIFE ON LAND
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
Documents
18
Citations
236
h-index
9
Documents
17
Citations
185
Scholarly Output
10
Articles
3
Views / Downloads
0/0
Supervised MSc Theses
2
Supervised PhD Theses
0
WoS Citation Count
57
Scopus Citation Count
74
WoS h-index
4
Scopus h-index
5
Patents
0
Projects
0
WoS Citations per Publication
5.70
Scopus Citations per Publication
7.40
Open Access Source
3
Supervised Theses
2
| Journal | Count |
|---|---|
| 2011 Ieee Congress on Evolutıonary Computatıon (Cec) | 1 |
| 2011 Ieee Symposıum on Dıfferentıal Evolutıon (Sde) | 1 |
| 2025 International Conference on Intelligent and Fuzzy Systems-INFUS-Annual -- Jul 29-31, 2025 -- Istanbul, Turkiye | 1 |
| Iıe Transactıons | 1 |
| Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | 1 |
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Now showing 1 - 10 of 10
Conference Object Citation - WoS: 7Citation - Scopus: 15A Discrete Artificial Bee Colony Algorithm for the Economic Lot Scheduling Problem(IEEE, 2011) Tasgetiren, M. Fatih; Bulut, Onder; Fadiloglu, M. MuratIn this study we present a discrete artificial bee colony (DABC) algorithm to solve the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. In specific, our algorithm provides a cyclic production schedule of n items to be produced on a single machine such that the production cycle of each item is an integer multiple of a fundamental cycle. All the integer multipliers are in the form of power-of-two, and under EBP approach feasibility is guaranteed with a constraint that checks if the items assigned in each period can be produced within the length of the period. For this problem, which is NP-hard, our DABC algorithm employs a multi-chromosome solution representation to encode power-of-two multipliers and the production positions separately. Both feasible and infeasible solutions are maintained in the population through the use of some sophisticated constraint handling methods. A variable neighborhood search (VNS) algorithm is also fused into DABC algorithm to further enhance the solution quality. The experimental results show that the proposed algorithm is very competitive to the best performing algorithms from the existing literature under the EBP and PoT policy.Conference Object Reinforcement Learning in Condition-Based Maintenance: A Survey(Springer International Publishing AG, 2025) Erdem, Gamze; Dincer, M. Cemali; Fadiloglu, M. MuratThis literature review examines the convergence of Reinforcement Learning (RL) and Condition-Based Maintenance (CBM), emphasizing the transformative impact of RL methodologies on maintenance decision-making in complex industrial settings. By integrating insights from a diverse array of studies, the review critically assesses the use of various RL techniques such as Q-learning, deep reinforcement learning, and policy gradient approaches in forecasting equipment failures, optimizing maintenance schedules, and reducing operational downtime. It outlines the shift from conventional, rule-based maintenance practices to adaptive, data-driven strategies that exploit real-time sensor data and probabilistic modeling. Key challenges highlighted include computational complexity, the extensive training data requirements, and the integration of RL models into existing industrial frameworks. Furthermore, the review explores literature on CBM within multi-component systems, where prevalent approaches include numerical analyses, Markov Decision Processes (MDPs), and case studies, all of which demonstrate notable cost reductions and decreased downtime. Relevant studies were identified through searches on databases such as Google Scholar, Scopus, and Web of Science. Overall, this review provides a comprehensive analysis of the current state and prospects of employing reinforcement learning in conditionbased maintenance, offering valuable insights for both academic researchers and industry practitioners.Article Citation - WoS: 20Citation - Scopus: 22An Embedded Markov Chain Approach To Stock Rationing(Elsevier Science Bv, 2010) Fadiloglu, Mehmet Murat; Bulut, OnderWe propose a new method for the analysis of lot-per-lot inventory systems with backorders under rationing. We introduce an embedded Markov chain that approximates the state-transition probabilities. We provide a recursive procedure for generating these probabilities and obtain the steady-state distribution. (C) 2010 Elsevier B.V. All rights reserved.Conference Object Citation - WoS: 3Citation - Scopus: 7A Differential Evolution Algorithm for the Economic Lot Scheduling Problem(IEEE, 2011) Tasgetiren, M. Fatih; Bulut, Onder; Fadiloglu, M. MuratIn this study we provide a Differential Evolution (DE) based heuristic to solve the Economic Lot Scheduling Problem (ELSP) under basic period approach. The problem is to find the best cyclic production schedule of n items to be produced on a single machine such that the production cycle of each item is an integer multiple of the basic period. The demand and the production rates are deterministic and known in advance. Our computational results suggest that our algorithm is competitive with the existing genetic algorithm, and therefore it is promising for the solution of a generalized version of the problem which is called extended basic period approach in the future.Article Citation - WoS: 11Citation - Scopus: 11An Efficient Procedure for Optimal Maintenance Intervention in Partially Observable Multi-Component Systems(Elsevier Ltd, 2024) Karabağ, O.; Bulut, Ö.; Toy, A.Ö.; Fadıloğlu, M.M.With rapid advances in technology, many systems are becoming more complex, including ever-increasing numbers of components that are prone to failure. In most cases, it may not be feasible from a technical or economic standpoint to dedicate a sensor for each individual component to gauge its wear and tear. To make sure that these systems that may require large capitals are economically maintained, one should provide maintenance in a way that responds to captured sensor observations. This gives rise to condition-based maintenance in partially observable multi-component systems. In this study, we propose a novel methodology to manage maintenance interventions as well as spare part quantity decisions for such systems. Our methodology is based on reducing the state space of the multi-component system and optimizing the resulting reduced-state Markov decision process via a linear programming approach. This methodology is highly scalable and capable of solving large problems that cannot be approached with the previously existing solution procedures. © 2023 The Author(s)Master Thesis Sales and Returns Forecasting for Inventory Control(İzmir Ekonomi Üniversitesi, 2013) Karabağ, Oktay; Eliiyi, Deniz Türsel; Fadıloğlu, Mehmet MuratGelişen çevre duyarlılığı, geleneksel üretim sistemlerini kullanan üreticileri yeni stratejiler benimsemeye zorlamaktadır. Piyasaya verilen ürünlerin kullanımlarından sonra toplanıp, işlenerek tekrar tüketiciye ulaştırılmasına, yeniden üretim (remanufacturing) ismi verilmektedir. Yeniden üretim sistemlerinde talep ve geri dönüş tahmini, satın alma kararları, üretim planlama ve envanter yönetimi vb. gibi yönetim konuları için vazgeçilemez öğelerdir. Bu çalışma, talep ve geri dönüş tahmini için yeni metotlar geliştirmeyi ve mevcut literatürü incelemeyi amaçlamaktadır. İlk olarak, talep tahmini için en bilindik ve uygulaması kolay olan HoltWinters metodu incelenmiştir. Ancak, Gregoryen ve Hicri takvim gibi iki asenkron takvimin ortak etkisi belirli bir pazarda kendini gösterdiğinde, bu metodun talep eğilimini yakalamakta yeterli olmadığı gerçeği fark edilmiştir. Bu nedenle, HoltWinters metodu iki asenkron takvim nedeniyle oluşan sezonluk etkiler dikkate alınarak geliştirilmiştir ve oluşturulan bu yeni yöntem Augmented HoltWinters metodu olarak adlandırılmıştır. İkinci olarak, geri dönüş tahmini için Kelle ve Silver tarafından geliştirilen metotlar incelenmiş ve farklı bir bakış açısıyla yeniden sunulmuşlardır. Kelle ve Silvera ait bu yöntemler durağan talep şartıyla sınırlandırıldıklarından, talebin durağan olmadığı durumlarda etkili olmayacaktır. Bu sorunu gidermek için, ilgili yöntemler durağan olmayan talebe izin veren daha gerçekçi bir bakış açısı ile revize edilmiştir. Son olarak, talep ve geri dönüşler için geliştirilen yeni tahmin yöntemleri önceki halleri ile gerçek zaman serisi kullanılarak karşılaştırılmıştır. Elde edilen sonuçlar, talep ve geri dönüş tahmini için önerilen yeni metotlar kullanıldığında önemli iyileştirmeler sağlanabileceğini göstermiştir.Conference Object Citation - Scopus: 1A Genetic Algorithm for the Economic Lot Scheduling Problem Under Extended Basic Period Approach and Power-Of Policy(2012) Bulut O.; Tasgetiren M.F.; Fadiloğlu, MuratIn this study, we propose a genetic algorithm (GA) for the economic lot scheduling problem (ELSP) under extended basic period (EBP) approach and power-of-two (PoT) policy. The proposed GA employs a multi-chromosome solution representation to encode PoT multipliers and the production positions separately. Both feasible and infeasible solutions are maintained in the population through the use of some sophisticated constraint handling methods. Furthermore, a variable neighborhood search (VNS) algorithm is also fused into GA to further enhance the solution quality. The experimental results show that the proposed GA is very competitive to the best performing algorithms from the existing literature under the EBP and PoT policy. © 2012 Springer-Verlag.Article Citation - WoS: 16Citation - Scopus: 18Production Control and Stock Rationing for a Make-To System With Parallel Production Channels(Taylor & Francis Inc, 2011) Bulut, Onder; Fadiloglu, Mehmet MuratThis article considers the problem of production control and stock rationing in a make-to-stock production system with lost sales, multiple servers in parallel production channels, and several customer classes. It is assumed that independent stationary Poisson demand streams and exponential service times are in operation. At decision epochs, the control specifies whether or not to increase the number of active servers in conjunction with the stock allocation decision. Previously placed production orders cannot be cancelled. The system is modeled as an M/M/s make-to-stock queue, and properties of the optimal cost function and of the optimal production and rationing policies are characterized. It is shown that the optimal production policy is a state-dependent base-stock policy, and the optimal rationing policy is of threshold type. Furthermore, it is shown that the rationing levels are non-increasing in the number of active channels. It is also shown that the optimal ordering policy transforms into a bang-bang type policy when the model is relaxed by allowing order cancellations. Another model with partial order-cancellation flexibility is provided to fill the gap between the no-flexibility and the full-flexibility models. The additional gain that the optimal policy provides over the suboptimal base-stock policy proposed in the literature is qualified along with the value of the flexibility to cancel production orders.Master Thesis Distribution and Inventory Policies for Raw Materials in a Process Industry(İzmir Ekonomi Üniversitesi, 2014) Dalgıç, Burcu; Sargut, Fatma Zeynep; Fadıloğlu, Mehmet MuratBu çalışmada, ana ambar ile koltuk ambarları arasındaki ham madde transferinin yönetimi hedeflenmektedir. Koltuk ambarları, üretim tesislerinin yanında bulunan malzeme (özellikle koltuk malzemeleri) stoklamak için kullanılan yerlerdir. Koltuk malzemeleri, üretilmekte olan partiyle ilgili ayar yapmak için kullanılan malzemelerdir. Bu malzemelerin eksikliği sebebiyle üretim esnasında duruşlar yaşanmaktadır. (s,Q) envanter politikası ile hangi malzemeden hangi koltuk ambarında ne kadar stok tutulması gerektiğine dair kararlar verilmektedir. Hedef, duruş sayısını ve süresini azaltarak siparişten sevkiyata olan çevrim süresini kısaltmaktır. Üretim esnasındaki duruşları en aza indirgeme ve toplam ekipman ve işgücü verimliliğini en fazlaya çıkarmak amacıyla, malzeme transferini milk run yöntemi ile (tedarikçi kontrollü envanter yönetimi prensibine göre) düzenleyen bir üretim lojistiği bölümü kurulması önerilmektedir.Conference Object Maintenance Decision and Spare Part Selection for Multi-Component System(Springer Science and Business Media Deutschland GmbH, 2024) Kaya, B.; Karabağ, O.; Fadıloğlu, M.M.Due to the advancement of technology over time, higher technology machines are being used in the production and service sectors. Companies suffer great financial losses if these machines stop working due to a breakdown. To avoid these losses, maintenance has become increasingly important for companies over time. Condition based maintenance aims to intervene in a system as close to the point of failure as possible using information received from the system. Sensors are used to obtain information about the wear and tear of the machine. However, since sensors are costly, they are not installed on every machine component but rather on the system. While this reduces costs, it also means that we now obtain partial information from the system rather than from each component. In these systems, we need to make two types of decisions. The first decision is when to intervene in the system. The second decision is how many spare parts to carry with us once we decide to intervene. We simulated several different experiments for a periodic system composed of identical components and found optimal policies based on the two decisions we made. Our managerial insights indicate that as the number of components in the machine increases, the importance of selecting spare parts for the system also increases, leading to a tendency to maintain the system as late as possible before the system fails. Moreover, in situations where the penalty for maintenance is lower after a failure occurs, in optimal policy, we maintain later and carry more spare parts during our interventions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
