Browsing by Author "Paldrak, Mert"

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Citation - Scopus: 2
A Firefly Algorithm for Bi-Objective Airport Gate Assignment Problem
(Springer Science and Business Media Deutschland GmbH, 2024) Mert Paldrak; Gamze Erdem; Mustafa Arslan Ornek; Paldrak, Mert; Örnek, Mustafa Arslan; Erdem, Gamze; N.M. Durakbasa , M.G. Gençyılmaz
The Airport Gate Assignment Problem (AGAP) is a challenging combinatorial optimization problem that arises in the efficient management of airport operations in daily basis. The task involves assigning arriving and departing aircrafts to appropriate gates within an airport terminal while maintaining safety and security of passengers along with various problem-specific constraints. Efficient gate assignment is of paramount importance for smooth airport operations since it directly affects such crucial factors as passenger flow aircraft turnover time gate utilization and overall airport capacity. The AGAP is rendered increasingly complex with factors such as multiple airlines varying aircraft sizes gate capacities maintenance requirements etc. In real life most hub-and-spoke airports have deals with numerous arriving and departing aircrafts and bridge-equipped gates. Consequently solving the AGAP requires tackling a complex combinatorial optimization task which cannot be solved using traditional optimization methods. In such cases metaheuristic algorithms have emerged as effective tools to address this NP-hard problem. In this study we employ a Firefly Optimization Algorithm to handle the AGAP in a reasonable amount of computational time. Firefly Optimization Algorithm is applied by formulating it as an optimization problem and aims to find an optimal gate assignment solution that maximizes total flight-to-gate assignment utility and minimizes numbers of flights assigned to apron. The algorithm is coded through MATLAB ® 2016 of a personal computer. The results obtained using Firefly Optimization Algorithm is compared to those solutions obtained through IBM ILOG CPLEX 12.0 Optimization Tool. © 2024 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
A GRASP Algorithm for Multi-objective Airport Gate Assignment Problem
(SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Mert Paldrak; Mustafa Arslan Ornek; Paldrak, Mert; Ornek, Mustafa Arslan; DP Sakas; A Kavoura; P Tomaras
The assignment of flights to appropriate gates is a complex combinatorial optimization problem that airport managers have to deal with every day. It is an important decision-making problem involving multiple and conflicting objectives. Considering the different stakeholders of the problem a multi-objective airport gate assignment problem is proposed and formulated as a Binary Integer Programming Model. This paper studies two main objectives namely maximizing total flight-to-gate assignment utility and minimizing total flight conflict probability. Unlike most of the mathematical models presented in the literature Airport Gate Assignment Problem is considered an over-constraint problem where flight-to-gate eligibility apron safety and night-stand flight constraints are involved. As a solution methodology a Greedy Randomized Adaptive Search Procedure (GRASP) algorithm on over-constrained AGAP is proposed since the algorithm produces a series of good features such as intuitive greedy appeals and is trivial to be efficiently implemented on parallel processors like gates. The paper aims to demonstrate the efficiency of the proposed solution methodology concerning determined objective functions.
Citation - WoS: 2
Citation - Scopus: 5
A 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 Sari
Given 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.
A Survey on Optimization Problems in the Airline Industry and Airports
(SPRINGER INTERNATIONAL PUBLISHING AG, 2024) Mert Paldrak; Melis Tan Tacoglu; Mustafa Arslan Ornek; Paldrak, Mert; Ornek, Mustafa Arslan; Tacoglu, Melis Tan; C Kahraman; SC Onar; S Cebi; B Oztaysi; AC Tolga; IU Sari
In response to the rapid growth in air transportation demand the methods to manage allocate and efficiently use scarce resources in the airport play a vital role in improving the efficiency of the air transportation system. Due to the limited infrastructure of hub-and-spoke airports which is influenced by many factors the chief goal of the airline industry and airport management is to utilize such resources as check-in desks departure lounges bridge-equipped gates aircraft stands baggage carousels staff and equipment. Based on the mobility of the resources in the airports there are two types of problems in the airline industry and airports namely mobile and immobile resource optimization problems. The crew optimization problems are mobile resource optimization problems whereas airport gate assignment counter assignment problems and carousel optimization problems are immobile resource optimization problems in airports. Considering the problems classified based on the mobility of the resources this paper aims to present a survey of optimization problems in the aviation industry explaining the interplay and relationship between these problems along with modeling techniques and proposed solutions to this individual problem.
Citation - WoS: 5
Citation - Scopus: 5
An Ensemble of Differential Evolution Algorithms with Variable Neighborhood Search for Constrained Function Optimization
(IEEE, 2016) Mert Paldrak; M. Fatih Tasgetiren; P. N. Suganthan; Quan-Ke Pan; Tasgetiren, M. Fatih; Suganthan, P. N.; Paldrak, Mert; Pan, Quan-Ke
In this paper an ensemble of differential evolution algorithms based on a variable neighborhood search algorithm (EDE-VNS) is proposed so as to solve the constrained real parameter-optimization problems. The performance of DE algorithms heavily depends on the mutation strategies crossover operators and control parameters employed. The proposed EDEVNS algorithm employs multiple mutation operators and control parameters in its VNS loops to enhance the solution quality. In addition we utilize opposition-based learning (OBL) to take advantages of opposite solutions to find a candidate solution which might be close to the global optimum. In addition we also present an idea of injecting some good dimensional values from promising areas in the population to the trial individual through the injection procedure. The computational results show that the EDE-VNS algorithm is very competitive to some of the best performing algorithms from the literature.
Citation - Scopus: 1
An International Hub Airport Selection Problem Using Fuzzy Analytic Hierarchy Process (F-AHP): Real Case Study in Turkey
(Springer Science and Business Media Deutschland GmbH, 2023) Melis Tan Tacoglu; Mert Paldrak; Mustafa Arslan Ornek; Caner Taçoğlu; Tan Taçoğlu, Melis; Paldrak, Mert; Taçoğlu, Caner; Örnek, Mustafa Arslan; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
In recent years air transportation volume has been significantly growing with the help of recent technological development related to the airline industry. Airline companies utilize their scarce resources such as aircraft crew and slot time based on airport regulation and capacity constraints efficiently to meet passenger demand, however the limited capacity of the airport’s immobile resources leads airlines to search for new hub alternatives. Hub selection is one of the most crucial decisions for airline companies’ strategy and also the selected hub’s future planning and operational strategy. This research aims to propose a solution method for selecting the best potential hub alternative among many potential hubs in a single hub system considering six main criteria: the potential hub’s city population the distance between the existing hub (İstanbul airport) the capacity the intensity the distance between city location and the accessibility. F-AHP is used as a solution methodology to evaluate each criterion and the proposed hubs. The computational experiment is conducted based on the potential twelve international airports in Turkey for the selection of an international hub airport considering the six aforementioned criteria. The results indicate that accessibility of the airport is the most crucial criterion among the six criteria and Izmir Adnan Menderes Airport is the best eligible alternative to be an international hub. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 3
Analytic 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. Gençyılmaz
In 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.
Application of Meta-heuristic Algorithms for Sequencing Multi-model Assembly Line with Sequence-Dependent Setup Time in Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2024) Tunahan Kuzu; Yaren Can; Elvin Sarı; Devin Duran; Sude Dila Ceylan; Mert Paldrak; Mustafa Arslan Ornek; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Örnek, Mustafa Arslan; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; N.M. Durakbasa , M.G. Gençyılmaz
This study provides an overview of the definition of long setup times and lateness due to the wide variety of models produced in the garment industry the solutions developed to solve these problems and the designs to be proposed. The setup times of the product produced in the Multi-Model Assembly Line vary according to the model type. In this study we considered a single machine as an assembly line and adapted Single Machine Scheduling with Sequence-Dependent setup times problem to Multi-Model Assembly Line Sequencing with sequence-dependent setup times problem for the garment industry. To solve this problem we used two different solution techniques: Meta-Heuristic Algorithms and a mathematical model that includes the setup process and lateness accordingly suggested. Two different metaheuristic algorithms Tabu Search and Simulated Annealing were used in this paper. SA algorithm Tabu Search Algorithm and mathematical model were used to find optimal and near-optimal results which were compared. The metaheuristic achieved favourable solutions when comparing the results with mathematical model results. The mathematical model suggested was solved utilizing version 20.1 of ILOG CPLEX OPTIMIZATION STUDIO. The simulated Annealing and Tabu Search algorithm suggested were solved utilizing version R2023a of MATLAB. The obtained results are compared with respect to solution quality and computational time. © 2024 Elsevier B.V. All rights reserved.
Citation - Scopus: 3
Applications 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. Gençyılmaz
In 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.
Çok kriterli havaalanı kapı ataması problemi için kısıt-bazlı çizelgeleme yaklaşımları
(2024) Paldrak, Mert; Örnek, Mustafa Arslan; Öztürk, Cemalettin
Havalimanı operasyonlarının alanında, kapı atamalarının etkili bir şekilde yönetilmesi her zaman kritik bir endişe olmuştur, bu durum doğrudan havalimanlarının, havayollarının verimliliğini ve yolcuların genel deneyimini etkilemektedir. Geleneksel olarak, Havalimanı Kapı Atama Problemi (AGAP) ve Havalimanı Kapı Yeniden Atama Problemi (AGRP) birbirinden ayrı varlıklar olarak ele alınmış ve her biri diğerinden bağımsız olarak ele alınmıştır. Ancak, bu geleneksel yaklaşım zamanla sınırlılıklarını ortaya koymuştur, havalimanı operasyonlarının öngörülemeyen doğası nedeniyle başlangıç kapı atamaları ile sonraki yeniden atamalar arasındaki dinamik etkileşimi yakalayamamıştır. Bu tez, AGAP ve AGRP'nin birbiriyle bağlantılılığını keşfederek ve kapı yönetimindeki karmaşıklıklar ve belirsizliklerle başa çıkmada etkili bir başlangıç programının kritik önemini vurgulayarak bu boşluğu kabul eder ve köprüler. Havalimanı kapı atamalarına dahil olan çok sayıda paydaş ve başlangıç kapı atamasının gerekli sağlamlığı göz önüne alındığında, bu araştırma, paydaş beklentilerini karşılamayı ve yeniden atama süreci boyunca programın istikrarını korumayı amaçlayan üç amaçlı bir problemi ele alır. Bu karmaşık çok amaçlı meseleyi ele almak için, tez, farklı amaçları ve belirli problem değişkenlerini, örneğin havalimanı yoğunluğunu, karşılamak üzere tasarlanmış bir dizi yapıcı sezgiyi, İkili Tamsayı Programlama (BIP), Kısıtlama Programlama (CP) ve Ağ Modelleme (NM) tanıtır. Ampirik analizler, geleneksel matematiksel modellerin optimal çözümleri uygulanabilir bir hesaplama zaman çerçevesi içinde sunmada yetersiz kaldığını ortaya koymaktadır. Matematiksel modellerin verimliliğini artırmak için, amaca özel geçerli eşitsizlikler de önerilmiştir. Buna karşılık, tasarlanan yapıcı sezgiler, karar verme sürecini kolaylaştıran etkili uzlaşı çözümleri üretmede etkilidir. Uçakların sıralanması ve önceden belirlenmiş kriterlere dayanarak kapıların seçilmesi sürecini içeren bir süreç yoluyla geliştirilen özel yapıcı sezgiler, etkili uzlaşı çözümleri hızlı bir şekilde üretebilme konusunda olağanüstü bir yeteneğe sahiptir. Çözüm manzarasını daha da zenginleştiren tez, Adaptif Büyük Komşuluk Arama (ALNS) ve Açgözlü Rastgele Uyarlanabilir Arama Prosedürü (GRASP) performansını daha basit sezgilerle karşılaştırır. Çok Amaç-Odaklı ve Havalimanı Yoğunluğu-Odaklı Yapıcı Sezgilerin, ALNS ve GRASP'in karmaşıklık ve hesaplama taleplerini sadece eşleştirmekle kalmayıp, yüksek kaliteli çözümleri etkin bir şekilde elde ederek bu daha maliyetli yöntemleri geride bıraktığı sonucuna varır. Havalimanı Kapı Yeniden Atama Problemini ele alırken, tez, minimum kapı değişikliği ve ceza tabanlı olmak üzere iki BIP modeli ile birlikte bir senaryo tabanlı stokastik yaklaşım önerir. Kapı Atama Probleminde elde edilen optimal bir başlangıç programının kritik önemi gösterilerek, Adnan Menderes Uluslararası Havalimanı'ndan gerçek bir senaryo, çeşitli yapıcı sezgiler kullanılarak başlangıç programları üretmek için analiz edilir. Daha sonra, bu programlar havalimanı kapı yeniden atama modellerinde kullanılarak, gerçek zamanlı programlamanın performansı üzerindeki etkileri değerlendirilir. Hesaplama bulguları, sağlamlık ve havalimanı yoğunluğuna odaklanarak hazırlanan başlangıç programlarının, yeniden atama aşamasında kapı değişikliklerini önemli ölçüde azaltabileceğini öne sürmektedir. Son olarak, tez, farklı uçuş varış ve kalkış senaryolarını inceleyerek, senaryolar arasında kapılara atanan uçuş sayısındaki farklılıkları en aza indirmek için çeşitli programlama tekniklerini kullanır.
Citation - Scopus: 1
Demand Forecasting and Inventory Control System for Industrial Valves
(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Efe Erol; Ataberk İnan; Deniz Fırat; Artun Erdoğan Miran; Ercan Çetinkaya; Işılay Nur Polat; Efthimia Staiou; Burçin Kasap; Pınar Aydın; Erol, Efe; Fırat, Deniz; İnan, Ataberk; Miran, Artun Erdoğan; Çetinkaya, Ercan; Paldrak, Mert; Aydın, Pınar; N.M. Durakbasa , M.G. Gençyılmaz
Forecasting customer demand for preliminary products in an accurate way plays a vital role in increasing efficiency of inventory control systems reducing total costs and meeting the requirements of customers on time. Considering this fact the chief objective of the study is to develop a user-friendly decision support system (DSS) to be able to forecast demand for products and minimize the cost of total inventory control costs including ordering and holding costs. Due to the complexity of the problem of this study the project is handled in two parts namely demand forecasting and inventory management. In the demand forecasting part unlike the traditional methods which mostly ignore the statistical behaviour of demand distribution of products we employed Holt-Winters and SARIMA techniques which minimize the error of forecasting by harnessing demand behaviour. In the second part the forecasted demand values are used as inputs for the inventory control system. In this part we developed a Mixed Integer Programming Model (MIP) where the total inventory cost involving ordering and holding costs is to be minimized. To solve the proposed mathematical model IBM CPLEX OPTIMIZER coupled with Branch & Bound Algorithm (B&B) is employed. In addition to this exact solution technique we also used the Benders Decomposition method which is suitable to solve MIP models in a more reasonable computational time with optimality by decomposing the model into master and sub-problem. Besides these two exact-solution techniques to determine the number of products to be ordered from a supplier in a shorter computational time when the problem size is larger a heuristic solution was developed adapted from the Silver Meal algorithm. The results obtained using the aforementioned techniques are compared concerning their solution quality and computational time. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
Developing a Spare Parts Demand Forecasting System
(Springer Science and Business Media Deutschland GmbH, 2020) Elif Özbay; Banu Hacialioğlu; Büşra İlayda Dokuyucu; Hakan Şahin; Mehmet Mukan Saçlı; Merve Nur Genç; Efthimia Staiou; Mert Paldrak; Şahin, Hakan; Hacialioğlu, Banu; Saçlı, Mehmet Mukan; Özbay, Elif; Paldrak, Mert; Dokuyucu, Büşra İlayda; Genç, Merve Nur; 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
The focus of this study is on developing a decision support system (DSS) in order to forecast spare parts demand for a company producing high technology products in Turkey. The company is one of the world’s leading original design manufacturers in the field of consumer electronics and white goods. Accurate forecasts of customer demand for preliminary products and spare parts play an important role in order to reduce costs and increase customer satisfaction. Currently the company’s forecasting system is based on personnel experience and a statistical approach which lacks the ability of capturing demand data behaviour. The approach followed results in an increased forecasting error thus increases production costs results in lack of spare parts and decreases customer satisfaction. The aim of this project is to develop a DSS to minimize the forecasting error, therefore help the company develop a policy for optimizing the stock levels kept reducing costs and increasing customer satisfaction. In order to understand the behaviour of customer demand of spare parts the company’s television products are chosen for the pilot study since these products are highly influenced by rapid technological changes and changes in the product models. The spare parts are classified into different groups using ABC analysis in order to develop a forecasting model for each group. In the solution methodology part three different statistical methodologies for the forecasting process were respectively studied, Winter’s Double Exponential Smoothing and Moving Average Methods. Winter’s Method is used for the data which exhibit trend and seasonality Double Exponential Smoothing is used for the data which exhibit trend and Moving Average Method is used for the data which exhibit stationary behaviour. In the DSS developed the above-mentioned methodologies are coded using Excel VBA programming language historical data’s behaviour is analysed and forecasts for future spare parts demand are made. The forecasting results are compared based on the minimum error (PAE) to decide upon which is the most appropriate forecasting methodology to use according to the specific spare parts past data behaviour. © 2022 Elsevier B.V. All rights reserved.
Fuzzy Goal Programming Approach to Multi-objective Facility Location Problem for Emergency Goods and Services Distribution
(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Simge Güçlükol Ergin; Gamze Erdem; Melis Tan Tacoglu; Paldrak, Mert; Tacoğlu, Melis Tan; Ergin, Simge Güçlükol; Erdem, Gamze; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
Ensuring the distribution of vital goods and services during emergency or post-disaster situations is crucial for meeting the needs of those affected as quickly as possible. The challenge lies in finding suitable and pertinent locations for facilities to efficiently distribute these goods and services. In such a situation location decisions for these facilities must be made considering multiple objectives. However in such a real-life problem the aspiration levels of each of the objectives are not certainly known due to unpredictable results of a disaster. Consequently the problem is formulated as fuzzy multi-objective facility location problem where two objectives are taken into consideration. We specifically consider minimization of total cost of facilities to be opened and minimization of total distance travelled by victims. Due to the conflicting nature of these objective functions we propose to employ two different fuzzy weighted goal programming techniques to find suitable compromise solutions for the problem. We present our developed models and provide results for three instances with different sizes. The proposed models are coded using IBM CPLEX Optimizer to obtain solutions in a reasonable amount of computational time. This paper contributes to the literature by providing two different fuzzy weighted goal programming techniques and comparing their efficiencies. © 2023 Elsevier B.V. All rights reserved.
Fuzzy Goal Programming Model for Sequencing Multi-model Assembly Line with Sequence Dependent Setup Times in Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Elvin Sarı; Mert Paldrak; Tunahan Kuzu; Devin Duran; Yaren Can; Sude Dila Ceylan; Mustafa Arslan Ornek; Başak Erol; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; Erol, Başak; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
In today’s competitive market the pressure on organizations to find ways to create value for customers and meet their requirements becomes stronger. In this manner clothing manufacturers focus on the production of various products with low stock to minimize their costs. In the garment industry assembly lines are commonly used production systems whose balance is the main concern of production managers. Meeting customer demand on-time is of outsized importance for the reputation of a clothing manufacturer and several objective functions must be considered simultaneously. In this study two objective functions namely minimization of setup times and minimization of lateness are handled to increase the efficiency of the assembly line and convenience to customers. A real-life problem in the garment industry is defined and formulated as a Fuzzy Goal Programming model since the aspiration levels of each objective are not certainly known. Two different Weighted Fuzzy Goal Programming Models are proposed and the proposed mathematical models are tackled with the help of ILOG IBM CPLEX OPTIMIZATION STUDIO version 20.1 and the solutions are interpreted from a decision-maker perspective. © 2023 Elsevier B.V. All rights reserved.
Fuzzy Model for Multi-objective Airport Gate Assignment Problem
(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Melis Tan Tacoglu; Mustafa Arslan Ornek; Paldrak, Mert; Örnek, Mustafa Arslan; Tacoglu, Melis Tan; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
To address the increasing demand for air transportation the management allocation and efficient utilization of limited airport resources such as bridge-equipped gates are of paramount importance to improve the efficiency of the air transportation system. Bridge-equipped gates are scarce and immobile resources have a significant impact on airport management airlines and passenger convenience when utilized properly. Hence the gate assignment problem is an important problem involving multiple stakeholders with conflicting objectives. This study proposes a fuzzy model to tackle two objectives: maximization of overall utility of flight-gate assignments and maximization of the robustness of the assignment schedule simultaneously. Fuzzy variables are employed in order to represent the uncertainty of idle times between two consecutive flights served by the same bridge-equipped gate and their membership degrees express their effect on assignment robustness. An adjustment function is applied to combine these two objective functions into one. To handle this NP-hard problem in a reasonable amount of computational time a constructive heuristic algorithm is employed. The performance of the proposed fuzzy model is evaluated with the help of various test in instances of different sizes Two fuzzy distribution functions are tested and their comparison is provided. The simulation results demonstrate the applicability and effectiveness of the fuzzy model in addressing multi-objective airport gate assignment problem. © 2023 Elsevier B.V. All rights reserved.
Fuzzy TOPSIS and Goal Programming Approaches to Multi Objective Facility Location Problem for Emergency Goods and Services Distribution and Bornova/Izmir Case Study
(Springer Science and Business Media Deutschland GmbH, 2022) Mert Paldrak; Simge Güçlükol Ergin; Mahmut Ali Gökçe; Melis Tan Tacoglu; Gökçe, Mahmut Ali; Tan Tacoğlu, Melis; Paldrak, Mert; Güçlükol, Simge; Tacoglu, Melis Tan; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
Distributions of vital goods and services in emergency or post disaster situations are of paramount importance to be able to meet the requirements of those in need on time. Finding an appropriate location for facilities to distribute such goods and services efficiently and quickly is an important challenge. In such a situation location decisions for these facilities must be made quickly considering multiple objectives. This problem is a multi-objective facility location problem (MOFLP). The main focus of this study is to present two solution methodologies for a MOFLP in a post disaster situation. We specifically consider objective of minimizing maximum weighted distance traveled and minimizing total cost of facilities to be opened in order to satisfy all demand. We also provide a version of the problem when the number of facilities to be opened is limited and second objective becomes maximizing demand covered. Due to the conflicting nature of the objective functions we propose to apply Fuzzy TOPSIS and Goal Programming and compare the solutions obtained using these two techniques with respect to solution quality and computational time. We present the developed models and provide results from a real-life application using existing emergency assembly areas and current census data for Bornova/İzmir. This paper contributes in two ways to existing literature. First is the comparison between multiple (two) solution methodologies for MOPLP. Studies in the literature provide only one solution technique such as Fuzzy TOPSIS Goal Programming etc. Secondly we implement these methodologies by using real life data for emergency situations. © 2022 Elsevier B.V. All rights reserved.
Gerçek parametre optimizasyonu için toplu diferensiyel evrim algoritması ve çok buyutlu sırt çantası problemine uygulanması
(2016) Paldrak, Mert; Taşgetiren, Mehmet Fatih
Bu tez, kısıtlanmış tek amaçlı test fonksiyonları aracılığı ile son dönemlerdeki gerçek parametre optimizasyon metotlarını incelenmiştir. Bu deneyimden esinlenerek, bu tür yöntemlerin aynı zamanda en zor ayrık problemlerden birisi olarak bilinen çok boyutlu sırt çantası problemine uygulanabilirliğini de ortaya koymuştur. Bu çalışmanın ilk bölümünde, CEC 2006'da ortaya konulan kıyaslama problemleri çözülmek üzere ele alınmıştır. Bu kıyaslama problemleri doğrusal olmayan amaç fonksiyonlarına sahip, çok boyutlu ve kısıtlanmış gerçek parametreli optimizasyon problemleridir. Bundan dolayı, sezgisel ve meta sezgisel yaklaşımları kullanmadan bu problemleri çözmek oldukça zordur. En iyi çözümler elde etmek için, önerilen algoritma (EDE-VNS) bu test fonksiyonlarına uygulanmıştır ve literatürdeki en iyi performansı gösteren algoritmalar ile karşılaştırılmış, rekabetçi sonuçlar elde edilmiştir. DE algoritmasının performansı çoğunlukla mutasyon stratejilerine, çaprazlama operatörlerine ve seçilmiş kontrol parametrelerine bağlıdır. Sonuç olarak, birden fazla mutasyon operatörleri ve kontrol parametrelerini kendi VNS döngüleri içerisinde bulundurabilen bir EDE-VNS algoritması çözümün kalitesini arttırabilmek amacıyla geliştirilmiştir. VNS döngüleri içindeki değişken mutasyon stratejilerinin toplu halde çalışmaları sayesinde, DE algoritmasının performansı o kadar olumlu etkilenmiştir ki çoğu kıyaslama problemleri sıfır standart sapma ile optimal olarak çözülmüştür. Mutasyon stratejilerinin toplu halde çalışmalarını etkisi göstermek için, bu test fonksiyonları bütün mutasyon stratejileri teker teker kullanılarak da çözülmüştür. Bireysel mutasyon stratejileri teker teker kullanıldığında, hepsi test fonksiyonlarında optimum çözümler bulma konusunda başarısız olduğu, oysaki bu mutasyon stratejileri toplu halde uygulandığında algoritma mutasyon stratejilerinin farklı özellikleri sayesinde optimal sonuçları kolaylıkla bulabildiği sonucuna varılmıştır. Bunun üzerine, bu algoritma aynı zamanda 240,000 ve 500,000 fonksiyon değerlendirilmesi ile çalıştırılmıştır. . Bu apaçık ortadadır ki, EDE-VNS algoritması ile daha çok optimal çözümler bulmak, daha fazla fonksiyon değerlendirilmesine ihtiyaç duyulmaktadır. Buna ek olarak, hedef bireylerin evrimini ve popülasyon içinde umut vadeden alanlardan alınan bazı iyi boyutlu değenlerin enjeksiyonunu temel alan çeşitlendirme yöntemi de, iki boyutlu turnuva seçilim yöntemi kullanılarak uygulanmıştır. Gelişmiş popülasyon içerisindeki uygun olmayan çözümlerden faydalanabilmek için, çözümü daha da geliştirmek amacıyla bazı kısıtlama işleme kuralları kullanılmıştır. Hesaplanan sonuçlar göstermektedir ki basit bir EDE-VNS algoritması literatürdeki bazı en iyi performansı gösteren algoritmalarla oldukça rekabetçidir. Bu tezin ikinci bölümünde, gerçek hayat problemlerinde geniş ölçüde uygulamaları olan 0-1 çok boyutlu sırt çantası probleminin, önerilen EDE-VNS algoritması ile çözülebileceği öngörülmüştür. Literatürde, çok boyutlu sırt çantası problemine uygulanan sezgisel yöntemlerin birçoğu, çözümleri geliştirmek için kontrol ve onarım operatörlerini kullanmıştır. Literatürde ortaya çıkan çalışmaların aksine, popülasyon çeşitliliğini zenginleştirmek için bazı gelişmiş kısıtlama işleme yöntemleri kullanılmıştır. Çeşitli toplu mutasyon stratejilerini kullanan değişken komşu aramalı diferansiyel evrim algoritması, deneme popülasyonunu oluşturmak için ortaya atılmıştır. Aslında önerilen bu EDE-VNS algoritması sürekli alanda çalıştığı için, gerçek değer kromozomları S-şeklindeki ve V-şeklindeki transfer fonksiyonlar kullanılarak 0-1 ikili değerlerine dönüştürülmüştür. Çözümleri geliştirmek için, EDE-VNS algoritmasıyla ikili takas yerel arama algoritması birleştirilmiş, önerilen algoritma OR-kütüphanesinden alınan karşılaştırma örnekleri üzerinde test edilmiştir.
Integrating Fuzzy AHP and TOPSIS for Optimal Air Fryer Selection: A Consumer-Centric Approach
(SPRINGER INTERNATIONAL PUBLISHING AG, 2024) Mert Paldrak; Fatma Nese Ozen; Berkin Yeginoglu; Cansu Bora; Armagan Yagiz Terim; Özen, Fatma Neşe; Yeginoğlu, Berkin; Paldrak, Mert; Terim, Armağan Yağız; Bora, Cansu; C Kahraman; SC Onar; S Cebi; B Oztaysi; AC Tolga; IU Sari
This study presents a novel methodology combining Fuzzy Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to aid consumers in selecting the most suitable air fryer. The decision-making process in choosing kitchen appliances like air fryers is often complex involving multiple criteria that can be challenging to assess and prioritize. Our approach utilizes Fuzzy AHP to determine the weights of various criteria based on consumer preferences ensuring a more accurate reflection of their importance. These criteria encompass factors such as price capacity energy efficiency user-friendly features and brand reputation which are critical in influencing consumer decisions. The integration of Fuzzy AHP with TOPSIS addresses the subjective and uncertain nature of consumer choices providing a structured and quantifiable method to evaluate and rank air fryers. This methodology not only captures the qualitative aspects of consumer preferences but also offers a comparative analysis of the products in the market. The result is a comprehensive decision-making tool that guides consumers through a balanced evaluation of the options leading to an informed and satisfactory purchase. By combining these two advanced decision-making techniques the study aims to significantly contribute to consumer behavior research and decision support systems offering a pragmatic solution for navigating complex market offerings and identifying an air fryer that aligns with specific needs and preferences.
Intelligent Benders’ Decomposition Algorithm for Sequencing Multi-model Assembly Line with Sequence Dependent Setup Times Problem: A Case Study in a Garment Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Elvin Sarı; Mert Paldrak; Yaren Can; Tunahan Kuzu; Sude Dila Ceylan; Devin Duran; Mustafa Arslan Ornek; Ozan Can Yıldız; Sarı, Elvin; Ceylan, Sude Dila; Can, Yaren; Kuzu, Tunahan; Duran, Devin; Paldrak, Mert; Yıldız, Ozan Can; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
In recent years clothing manufactures aim at producing various of products with low stock in order to meet customer demand. Besides this fact the ready-made clothing industry needs to pursue science technology and innovation policies to keep up with the rapid change in the fashion industry. One of the most commonly used production systems in garment industry is assembly lines where parts are subsequently added until the end product is obtained. In garment industry on time delivery plays a vital role in increasing customer satisfaction while ensuring demand. Consequently setup times in assembly lines are of paramount importance to track the performance of production system. In this study the minimization problem of long setup times due to the wide variety of models produced in the garment industry is handled. A real-life production management problem is defined formulated as an MIP model and solved to improve customer delivery rate and to increase efficiency by minimizing setup time. To solve this problem to optimality two exact solution techniques namely Branch and Bound and Benders’ Decomposition Techniques are taken into consideration. The proposed mathematical model is solved with ILOG CPLEX OPTIMIZATION STUDIO version 20.1 and the solutions obtained using each technique are compared with respect to solution quality and computational time. © 2023 Elsevier B.V. All rights reserved.
Mathematical Optimization and Fuzzy AHP for Efficient Warehouse Storage and Product Management
(Springer Science and Business Media Deutschland GmbH, 2025) Bartu Çatal; Bartu Taskin; Atakan Bitik; Elif Sena Kalkan; Doğuhan Şen; Mert Paldrak; Bitik, Atakan; Taskin, Bartu; Catal, Bartu; Kalkan, Elif Sena; Sen, Doguhan; Paldrak, Mert; C. Kahraman , B. Oztaysi , S. Cebi , S. Cevik Onar , C. Tolga , I. Ucal Sari , I. Otay
This study focuses on mathematical modeling and optimization solutions for storage problems specifically regarding warehouse shelving and product management. A mathematical model was developed to analyze the arrangement of shelves and products with the aim of maximizing efficiency and optimal space usage. In this model warehouse shelf placement and capacity constraints were determined while considering cost minimization and effective space utilization. The model was then solved using optimization tools. Additionally an ABC analysis was conducted to prioritize products within the warehouse employing the Analytic Hierarchy Process (AHP) method to rank the items based on their importance. The AHP method allowed for a systematic evaluation of criteria such as demand value and turnover rate enabling more efficient decision-making. The results of this study highlight the potential improvements in warehouse management offering a structured approach to both shelf arrangement and product prioritization. The proposed model and analysis method contribute to increasing operational efficiency reducing costs and optimizing logistical processes in warehouse management. © 2025 Elsevier B.V. All rights reserved.