Staiou, Efthymia
Loading...
Name Variants
Job Title
Dr.Öğr.Üyesi
Email Address
Main Affiliation
01.01.09.03. Endüstri Mühendisliği Bölümü
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
1NO POVERTY
0
Research Products
2ZERO HUNGER
0
Research Products
3GOOD HEALTH AND WELL-BEING
0
Research Products
4QUALITY EDUCATION
0
Research Products
5GENDER EQUALITY
0
Research Products
6CLEAN WATER AND SANITATION
2
Research Products
7AFFORDABLE AND CLEAN ENERGY
0
Research Products
8DECENT WORK AND ECONOMIC GROWTH
0
Research Products
9INDUSTRY, INNOVATION AND INFRASTRUCTURE
3
Research Products
10REDUCED INEQUALITIES
0
Research Products
11SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
12RESPONSIBLE CONSUMPTION AND PRODUCTION
1
Research Products
13CLIMATE ACTION
2
Research Products
14LIFE BELOW WATER
0
Research Products
15LIFE ON LAND
1
Research Products
16PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
17PARTNERSHIPS FOR THE GOALS
1
Research Products
Documents
12
Citations
40
h-index
3
Documents
5
Citations
20
Scholarly Output
10
Articles
1
Views / Downloads
0/3
Supervised MSc Theses
0
Supervised PhD Theses
0
WoS Citation Count
20
Scopus Citation Count
38
Patents
0
Projects
0
WoS Citations per Publication
2.00
Scopus Citations per Publication
3.80
Open Access Source
1
Supervised Theses
0
| Journal | Count |
|---|---|
| 21st International Symposium on Production Research (ISPR) - Digitizing Production System | 3 |
| 24th International Symposium for Production Research ISPR 2024 | 2 |
| International Symposium for Production Research ISPR 2023 | 2 |
| 4th International Conference on Intelligent and Fuzzy Systems (INFUS) | 1 |
| International Symposium for Production Research ISPR 2020 | 1 |
Current Page: 1 / 2
Scopus Quartile Distribution
Quartile distribution chart data is not available
Competency Cloud
10 results
Scholarly Output Search Results
Now showing 1 - 10 of 10
Article Citation - WoS: 17Citation - Scopus: 21Enhancing Meteorological Drought Modeling Accuracy Using Hybrid Boost Regression Models: A Case Study from the Aegean Region Türkiye(Multidisciplinary Digital Publishing Institute (MDPI), 2023) Enes Gul; Efthimia Staiou; Mir Jafar Sadegh Safari; Babak Vaheddoost; Vaheddoost, Babak; Safari, Mir Jafar Sadegh; Gul, Enes; Staiou, EfthymiaThe impact of climate change has led to significant changes in hydroclimatic patterns and continuous stress on water resources through frequent wet and dry spells. Hence understanding and effectively addressing the escalating impact of climate change on hydroclimatic patterns especially in the context of meteorological drought necessitates precise modeling of these phenomena. This study focuses on assessing the accuracy of drought modeling using the well-established Standard Precipitation Index (SPI) in the Aegean region of Türkiye. The study utilizes monthly precipitation data from six stations in Cesme Kusadasi Manisa Seferihisar Selcuk and Izmir at Kucuk Menderes Basin covering the period from 1973 to 2020. The dataset is divided into three sets training (60%) validation (20%) and testing (20%) sets. The study aims to determine the SPI-3 SPI-6 and SPI-12 using a multi-station prediction technique. Three boosting regression models (BRMs) namely Extreme Gradient Boosting (XgBoost) Adaptive Boosting (AdaBoost) and Gradient Boosting (GradBoost) were employed and optimized with the help of the Weighted Mean of Vectors (INFO) technique. Model performances were then evaluated with the Root Mean Square Error (RMSE) Mean Absolute Error (MAE) Mean Absolute Percentage Error (MAPE) Coefficient of Determination (R2) and the Willmott Index (WI). Results demonstrated a distinct superiority of the XgBoost model over AdaBoost and GradBoost in terms of accuracy. During the test phase the XgBoost model achieved RMSEs of 0.496 0.429 and 0.389 for SPI-3 SPI-6 and SPI-12 respectively. The WIs were 0.899 0.901 and 0.825 for SPI-3 SPI-6 and SPI-12 respectively. These are considerably lower than the corresponding values obtained by the other models. Yet the comparative statistical analysis further underscores the effectiveness of XgBoost in modeling extended periods of drought in the Aegean region of Türkiye. © 2023 Elsevier B.V. All rights reserved.Conference Object Scheduling for Parallel Plastic Injection Machines: A Sustainable Approach Using Goal Programming(Springer Science and Business Media Deutschland GmbH, 2025) Beril Durmaz; Ferit Doğruel; Beste Atasolmaz; Doruk Dumlu; Seray Tütüncü; Mert Paldrak; Efthimia Staiou; Durmaz, Beril; Tütüncü, Seray; Atasolmaz, Beste; Paldrak, Mert; Doğruel, Ferit; Dumlu, Doruk; Staiou, Efthymia; N.M. Durakbasa , K.G. GülenIn the dynamic manufacturing landscape efficient scheduling of parallel plastic injection machines is critical for optimizing production efficiency minimizing resource wastage and enhancing sustainability. This study addresses inefficiencies in manual job scheduling at a leading electrical components manufacturer with a focus on extended setup times and significant raw material losses during frequent color changes. The proposed solution uses Goal Programming techniques—specifically Weighted Goal Programming Tchebychev Goal Programming and Lexicographic Goal Programming—to develop an optimal scheduling model. The focus is on minimizing raw material loss and total setup time. All instances of the problem were solved using IBM ILOG CPLEX Version 22.1 ensuring robust and efficient solutions. This study aims to establish a benchmark for sustainable manufacturing practices by comparing these different Goal Programming approaches in terms of efficiency and effectiveness in real-world scheduling problems. © 2025 Elsevier B.V. All rights reserved.Conference Object Water Resource Management Using a Multiperiod Water Pricing Model in Izmir District(SPRINGER-VERLAG SINGAPORE PTE LTD, 2022) Zeynep Irem Ozen; Berk Sadettin Tengerlek; Damla Yuksel; Efthymia Staiou; Levent Kandiller; Yüksel, Damla; Özen, Zeynep İrem; Tengerlek, Berk Sadettin; Staiou, Efthymia; Kandiller, Levent; NM Durakbasa; MG GencyilmazWater is a product that cannot be substituted for living creatures to survive. The availability of water resources is crucial. The balance of water availability can change with environmental factors and as a result living creatures struggle with water scarcity. This study includes the policy of water pricing in the Izmir district. A multiperiod water pricing model based on transportation and inventory carrying problems is developed for encouraging water consumption reduction. Different pricing policy scenarios are proposed using the developed model to provide sustainable water management and penalize high water use. The aim is to maximize consumer welfare and ensure fair distribution among groups.Conference Object Citation - Scopus: 3Applications of Statistical Process Control Quality Improvement Tools and Techniques and a Simulation Model in a Garment Manufacturing Company(Springer Science and Business Media Deutschland GmbH, 2024) Pınar Erdinç; Zeynep Buduneli; Ceylin Erton; Çağla Gerşil; Mert Paldrak; Efthimia Staiou; Erton, Ceylin; Erdinç, Pınar; Paldrak, Mert; Gerşil, Çağla; Staiou, Efthymia; Buduneli, Zeynep; N.M. Durakbasa , M.G. GençyılmazIn the dynamic landscape of contemporary industrial production achievement in consistent product quality is of a paramount importance for any manufacturing enterprise. Among the various industries that require precision and attention to detail the garment manufacturing sector stands as a prime example. In this context this study aims to improve the process of detection and prevention of substandard fabrics entering the production process in a garment manufacturing company. The study utilizes statistical process control techniques such as the Individual-Moving Range (I-MR) control charts to monitor fabric critical-to-quality characteristics. Furthermore acceptance sampling methods are implemented to ensure that only fabrics meeting specifications are accepted for production. Additionally the project addresses sewing-related issues by improving the quality control checkpoints along the sewing line by using simulation. By conducting experiments within the simulated environment different quality control checkpoint configurations are tested to identify the most effective setup. The findings contribute to enhancing quality management practices in fabric procurement and sewing line operations minimizing financial losses improving customer satisfaction and ultimately bolstering the competitiveness of the garment manufacturing company. Furthermore the results shed light on the benefits of using Arena simulation for conducting comprehensive and cost-effective quality control evaluations. © 2024 Elsevier B.V. All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 4Spare Parts Inventory Management System in a Service Sector Company(SPRINGER-VERLAG SINGAPORE PTE LTD, 2022) Buse Atakay; Ozge Onbasili; Simay Ozcet; Irem Akbulak; Hatice Birce Cevher; Humeyra Alcaz; Ismail Gordesli; Mert Paldrak; Efthimia Staiou; Ozcet, Simay; Alcaz, Humeyra; Cevher, Hatice Birce; Onbasili, Ozge; Atakay, Buse; Akbulak, Irem; Staiou, Efthimia; NM Durakbasa; MG GencyilmazSpare parts inventory management is crucial in the success of a service providing company. In this study the spare parts of a service provider in the automotive sector are classified according to their characteristics in groups and different inventory control policies are applied to the categorized groups. The Analytical Hierarchy Process (AHP) one of the Multi-Criteria Decision Making (MCDM) methods is used to classify the spare parts into groups. As a result of the application of AHP classes of spare parts are determined according to the VED analysis classifying the spare parts according to their criticality. Furthermore the ABC analysis performed by the company was improved by using cost and demand criteria. After performing both analysis three new classes of spare parts are determined with the combination of ABC and VED classification techniques. For each class an appropriate inventory control policy is decided according to the spare parts importance and criticality. Based on the literature review the (R S s) inventory control policy is chosen to be applied in each class taking into consideration the review period order up-to-level and reorder point of items. In the inventory control model the review period for the same class items is assumed to be constant based on the information provided by the company. For verification purposes necessary cost calculations including total ordering and holding costs are performed by means of Microsoft Excel. In order to be able to vastly observe the system behavior different cost scenarios are generated by increasing and decreasing the service level and review period of the system. Using OptQuest an optimization tool embedded into ARENA simulation software the different scenarios were analyzed and the total minimum cost is reached. For supporting the daily operations of the company a user-friendly decision support system is built where the end-user can easily add/remove spare parts to/from the system classify them and compare the results of inventory control policies with the current system. The DSS will also assist the company to manage and control their real-time inventory and perform spare parts stock level tracking and decide when to place orders.Conference Object Citation - WoS: 2Citation - Scopus: 5A Literature Review on Supplier Selection Problem and Fuzzy Logic(SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Mert Paldrak; Gamze Erdem; Melis Tan Tacoglu; Simge Guclukol; Efthimia Staiou; Tan Tacoğlu, Melis; Paldrak, Mert; Guclukol, Simge; Staiou, Efthimia; Tacoglu, Melis Tan; Erdem, Gamze; C Kahraman; AC Tolga; SC Onar; S Cebi; B Oztaysi; IU SariGiven the recent increasing competition in global market supplier selection and evaluation has attracted a great deal of attention especially at academic levels. Supplier selection problem is a complex problem since there exist a great number of unpredictable and uncontrollable factors which have a huge impact on decision-making process. Due to this complexity there are several criteria that must be taken into consideration such as cost quality on-time delivery proximity of suppliers long-term relationship etc. Although some of these criteria (quantitative) can be expressed using pure numeric scales some (qualitative) are linguistic due to the human assessments which contain some degree of subjectivity. Since involvement of human assessment causes vagueness for deterministic models the authors apply fuzzy logic which enables the decision makers to be able to convert their linguistic expressions into fuzzy numbers with the help of fuzzy membership functions. Considering that fuzzy logic plays a vital role in solving multi-criteria supplier selection problem this paper aims to present a review of supplier selection problem and its relation with fuzzy logic. In this paper several studies that highlight supplier selection problem and the importance of fuzzy logic involvement in the problem have been reviewed. An analysis of multi-criteria decision-making methods for supplier selection problem is conducted.Conference Object Citation - Scopus: 3Analytic Hierarchy Process (AHP) and Goal Programming Approach for a Real-Life Supplier Selection Problem(Springer Science and Business Media Deutschland GmbH, 2024) Pınar Erdinç; Zeynep Buduneli; Çağla Gerşil; Ceylin Erton; Mert Paldrak; Efthimia Staiou; Erton, Ceylin; Erdinç, Pınar; Paldrak, Mert; Gerşil, Çağla; Staiou, Efthymia; Buduneli, Zeynep; N.M. Durakbasa , M.G. GençyılmazIn today’s intricate and competitive business environment the selection of suppliers plays a pivotal role in determining the success and efficiency of a company’s operations. Supplier selection is a multifaceted decision-making process that involves evaluating and comparing various factors such as quality cost lead time and reliability. To address the complexities inherent in this process organizations turn to advanced decision support methodologies. This study delves into a real-life supplier selection problem and explores the application of two prominent decision-making approaches: the Analytic Hierarchy Process (AHP) and Goal Programming. AHP provides a structured framework for systematically analysing complex decision criteria and preferences while Goal Programming facilitates the optimization of multiple conflicting objectives. The objective is the integration of AHP and Goal Programming to offer decision-makers a robust framework for analysing prioritizing and optimizing complex supplier selection problems. Effective supplier evaluation is crucial for the success of garment manufacturing facilities as it impacts the quality cost and timely delivery of raw materials and supplies required for production. AHP provides a structured approach to decision-making by breaking down complex decisions into a hierarchy of criteria and alternatives and enabling decision-makers to assign weights to each criterion based on their relative importance. Goal Programming on the other hand is a mathematical programming technique that helps decision-makers to find the best possible solution that satisfies multiple often conflicting objectives. This integration enables them to achieve a balanced and well-informed decision-making process aligned with the strategic goals and objectives of the organization. The combination of AHP and Goal Programming can provide a powerful decision-making framework for evaluating suppliers in garment manufacturing facilities. © 2024 Elsevier B.V. All rights reserved.Conference Object Drought Modelling Using Artificial Intelligence Algorithms in Izmir District(SPRINGER-VERLAG SINGAPORE PTE LTD, 2022) Zeynep Irem Ozen; Berk Sadettin Tengerlek; Damla Yuksel; Efthymia Staiou; Mir Jafar Sadegh Safari; Yüksel, Damla; Safari, Mir Jafar Sadegh; Özen, Zeynep İrem; Tengerlek, Berk Sadettin; Staiou, Efthymia; NM Durakbasa; MG GencyilmazThe world's water resources are decreasing day by day due to factors such as climate change drought inefficient pricing policies implemented by the government population growth uncontrolled water consumption technological developments and industrialization. A decrease in water resources causes water scarcity in the long-term period. This study is conducted to analysis the meteorological drought in Izmir district Turkey. Inspired by the real-life problem drought estimation models are developed through artificial neural network-based artificial intelligence techniques incorporating a decision support system. The Z-score index (ZSI) values are computed using precipitation data collected from five meteorological station in Kucuk Menderes basin and several developed models are compared according to the variety of statistical performance metrics.Conference Object Mixed Fleet Vehicle Routing Problem with Time Windows for Milk Collection(Springer Science and Business Media Deutschland GmbH, 2025) Melis Özveri; Yasemin Eda Üstün; Dilara Gürsesli; Koray Baysal; Şükran Dirik; Yağmur Leman Özdemir; Mert Paldrak; Efthimia Staiou; Üstün, Yasemin Eda; Özdemir, Yağmur Leman; Dirik, Şükran; Özveri, Melis; Staiou, Efthymia; Gürsesli, Dilara; Baysal, Koray; N.M. Durakbasa , K.G. GülenThis study conducted for a leading dairy company in Türkiye aimed to optimize the milk collection process by addressing the Vehicle Routing Problem (VRP) which is essential for the efficient collection of perishable products like milk in the dairy industry. Key constraints considered included vehicle capacity the number of vehicles milk quality collection time windows delivery speed route optimization and cost minimization. A mathematical model was initially developed and solved using IBM ILOG CPLEX, however as the number of collection locations increased solution times became impractical. To overcome this challenge the Benders Decomposition Algorithm was employed significantly improving solution efficiency. The application of this method led to enhanced collection efficiency and cost-effectiveness delivering substantial operational benefits to the dairy company. © 2025 Elsevier B.V. All rights reserved.Conference Object Citation - Scopus: 2A Parallel Machine Scheduling Problem for a Plastic Injection Company(Springer Science and Business Media Deutschland GmbH, 2021) Aytaç Ali Aslaner; Akdeniz Coşkun; Nur İlayda Tülemiş; Ece Özboyacı; Nil Ergün; Berk Bulut; Görkem Gülbent; Mert Paldrak; Efthimia Staiou; Aslaner, Aytaç Ali; Ergün, Nil; Bulut, Berk; Özboyacı, Ece; Staiou, Efthymia; Coşkun, Akdeniz; Tülemiş, Nur İlayda; N.M. Durakbasa , M.G. GençyılmazIn this study a production planning and scheduling problem is carried out in a company operating in the plastic injection sector in Turkey. The scheduling problem is classified as unrelated parallel machine scheduling problem with sequence dependent setup times including job-machine eligibility common source and precedence constraints. The proposed solution methodology is based on weekly planning with order grouping and makespan minimization. As a result a mixed integer programming model was formulated and optimal results are obtained for a sample data set with real data received. A user-friendly Decision Support System (DSS) was created to help the company with the weekly production planning and scheduling process applying a heuristic approach solution. © 2020 Elsevier B.V. All rights reserved.
