Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11290

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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.
Citation - WoS: 1
A Discrete-Time Resource Allocated Project Scheduling Model
(Springer Science and Business Media Deutschland GmbH, 2021-11-11) Berkay Çataltuğ; Helin Su Çorapcı; Levent Kandiller; Fatih Kağan Keremit; Giray Bingöl Kırbaş; Özge Ötleş; Atakan Özerkan; Hazal Tucu; Damla Yüksel; Yuksel, Damla; Cataltug, Berkay; Corapci, Helin Su; Keremit, Fatih Kagan; Otles, Ozge; Kirbas, Giray Bingol; Kandiller, Levent; N.M. Durakbasa , M.G. Gençyılmaz
Project Management involves the implementation of knowledge and skills to meet project requirements with beneficial tools and techniques. Project Management consists of tools that provide improvement in the pillars of time cost and quality. Discrete-Time Resource Allocated Project Scheduling Model (DTRAPS) is developed to minimize time to maximize quality and to minimize the cost of a project together in one tool. By means of this tool it is possible to allocate the resources over the project tasks in an optimized way with respect to each pillar of the triangle. Moreover sensitivity analysis on the model is done with the number of activities resource number and available time window parameters. The results indicate that the model is robust. Since the model is taking a longer CPU time in solving large problems heuristics such as Greedy Smallest Requirements First (SRF) Largest Requirements First (LRF) and Randomized are developed together with Swap improvement algorithm. Heuristics are compared and analyzed. Last of all a dynamic and user-friendly decision support system is developed on Excel-VBA for the model solution via CPLEX solver and heuristics. © 2022 Elsevier B.V. All rights reserved.
A DSS for Competency-Based Workforce Scheduling for Multi-production Lines
(Springer Science and Business Media Deutschland GmbH, 2023) Ziya Arsan; Bilge Bayrak; Selin Kader; Bilge Özen; Mert Turan Sarıca; Batuhan Türkan; Ege Duran; Levent Kandiller; Bayrak, Bilge; Özen, Bilge; Sarıca, Mert Turan; Kader, Selin; Arsan, Ziya; Kandiller, Levent; Türkan, Batuhan; N.M. Durakbasa , M.G. Gençyılmaz
Today effective workforce scheduling is crucial for companies. This paper presents a workforce scheduling problem for multiple production lines. This study aims to develop an efficient and methodological shift scheduling algorithm for a heating device plant to reduce unnecessary overtime and improve quality and performance. The workers are assigned to the stations based on their qualification rates and a line balancing option is provided if required. After linearizing the non-linear objective function using an innovative approach the mathematical model is developed and solved by OPL CPLEX STUDIO IDE 12.10.0. With toy and original data. The mathematical model is verified and validated and the results provide the optimal assignment of the workers to maximize the quality of lines. Since the company cannot use CPLEX due to license restrictions the mathematical model is integrated into the Python program using the Pulp library to provide a solver option to the company. Moreover the Hungarian method is coded in Python to create an instant solution. Since the company prefers to assign the workers manually a greedy method is developed to improve the manual solution. Finally a user-friendly Decision Support System is designed to support the decision-making processes. © 2023 Elsevier B.V. All rights reserved.
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 Flexible Facility Layout Design for a Project-Based Production System
(Springer Science and Business Media Deutschland GmbH, 2023) Elif Ceyhan; Yaren Özkan; Elif Şener; Gül Zozan Çetin; Hilal Toptanış; Özge Sevim Aykut; Selen Burçak Akkaya; Erdinc Oner; Çetin, Gül Zozan; Aykut, Özge Sevim; Özkan, Yaren; Öner, Erdinç; Ceyhan, Elif; Toptanış, Hilal; Şener, Elif; N.M. Durakbasa , M.G. Gençyılmaz
In this study the facility layout of a packaging machine production factory is planned according to the costs of the material handling equipment and distances between the departments. The branch and bound algorithm are implemented to optimally find the cells to be assigned for the projects. Costs are calculated in Excel and an optimal layout is developed in the facility according to the distances and the material handling costs information provided by the company. Moreover a decision support system is developed to display a flexible facility layout design for a project-based production system which provides insight for the managers to decide the locations of packaging machine production cells. The locations of the projects to the manufacturing cells are determined by using the algorithms and models using the Python and OPL CPLEX 12.10 Optimization Studio software. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
A Framework of Route Selection for Hazardous Goods Transportation in Tunnels
(Springer Science and Business Media Deutschland GmbH, 2019-10-25) Ayça Türkmen; Berna Özçınar; Gökay Aydoğdu; Tilbe Adsız; Melisa Ozbiltekin-Pala; Türkmen, Ayça; Aydoğdu, Gökay; Özçınar, Berna; Adsız, Tilbe; Özbiltekin, Melisa; 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
Due to the increase in globalization higher customer expectations and environment volatility supply chains are exposed to risks more easily. Therefore supply chain risk management become a crucial issue for companies and countries in last decades. Supply chain risk management (SCRM) involves all type of risks such as supplier risks locational risks natural risks. Hazardous goods transport is a very destructive type of transport which causes very risky accidents. Hazardous goods transport risks can have serious consequences for the environment property or people. The importance of these substances in daily life and industrialization and the increasing demand for these products are important for minimizing and assessing the risks associated with Dangerous Goods Transportation (DGT). Assets that may be affected by these risks are classified under 5 main criteria in this research. As a result of the Analytic Hierarchy Process (AHP) method it is aimed to help the selection by establishing a risk-based superiority between alternative ways and tunnels while selecting the route in the pilot area. © 2022 Elsevier B.V. All rights reserved.
A Genetic Algorithm for a Real-Life Scheduling Problem in the Valve Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Gamze Esma Bektaş; Ege Cömert; Ezgi Sena Yılmaz; Melis Tan Tacoglu; Önder Bulut; Burçin Kasap; Pınar Aydın; Mustafa İnceoğlu; Eda Badak; Hasan Şenol; Yılmaz, Ezgi Sena; Taçoğlu, Melis; Bulut, Önder; Bektaş, Gamze Esma; Cömert, Ege; Kasap, Burçin; Özcureci, Kaan; N.M. Durakbasa , M.G. Gençyılmaz
In this paper a real-life flexible job shop scheduling problem (FJSSP) for valve production having sequence-dependent setup times and machine unavailability constraints is studied. The aim is to minimize the weighted sum of earliness and tardiness of the scheduled jobs. Since this problem is known to be in the NP-Hard class we develop a Genetic Algorithm (GA) enriched with Iterated Local Search (ILS) to obtain near-optimal solutions for both the company’s problem and also for much larger instances in a reasonable run time. For the real-life implementation we develop a user-friendly Decision Support System (DSS) consisting of databases for the inputs a GA algorithm embedded as Python code and a Gantt Chart representation of solutions as the output. © 2023 Elsevier B.V. All rights reserved.
Citation - Scopus: 10
A genetic algorithm to solve the multidimensional Knapsack problem
(Association for Scientific Research membranes@mdpi.com, 2013-12-01) Murat Erşen Berberler; Asli Guler; Urfat Nuriyev; Berberler, Murat Ersen; Guler, Asli; Nuriyev, Urfat G.
In this paper The Multidimensional Knapsack Problem (MKP) which occurs in many different applications is studied and a genetic algorithm to solve the MKP is proposed. Unlike the technique of the classical genetic algorithm initial population is not randomly generated in the proposed algorithm thus the solution space is scanned more efficiently. Moreover the algorithm is written in C programming language and is tested on randomly generated instances. It is seen that the algorithm yields optimal solutions for all instances. © 2020 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
A Hybrid Decision Model for Balancing the Technological Advancement Human Intervention and Business Sustainability in Industry 5.0 Adoption
(Springer Science and Business Media Deutschland GmbH, 2023-10-02) Rahul Sindhwani; Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Ayça Maden; Maden, Ayca; Sindhwani, Rahul; Mangla, Sachin Kumar; Kazancoglu, Yigit; Z. Şen , O. Uygun , C. Erden
In Industry 5.0 humans and machines work together using advanced technologies like Artificial Intelligence (AI) the Internet of Things (IoT) and automation to improve efficiency productivity and quality while also supporting sustainable practices and human values. There is a growing interest in learning about the challenges of Industry 5.0 and exploring these technologies to promote sustainability and responsible business practices. We need a hybrid decision model to strike a balance between technical progress human values and sustainable practices as we move toward Industry 5.0 which presents enormous challenges in the areas of technology the environment society and ethics and business and economics. Through a literature analysis guided by the PRISMA technique and the Delphi method the study highlighted challenges in the areas of technology the environment society and ethics and business and economics as well as solution measures to address them. The weightage of the challenges was determined using the Best Worst Method and the ranking of the potential solutions was prioritized using the Elimination and Choice Expressing Reality method. © 2023 Elsevier B.V. All rights reserved.
A Hybrid Flow Shop Scheduling Problem
(Springer Science and Business Media Deutschland GmbH, 2019-10-25) Ayşegül Eda Özen; Gülce Çini; Merve Çamlıca; Nilay Çınar; Hasan Bahtiyar Soydan; Levent Kandiller; Hande Oztop; Çini, Gülce; Özen, Ayşegül Eda; Çamlıca, Merve; Kandiller, Levent; Öztop, Hande; Çınar, Nilay; Soydan, Hasan Bahtiyar; N.M. Durakbasa , M.N. Osman Zahid , R. Abd. Aziz , A.R. Yusoff , N. Mat Yahya , F. Abdul Aziz , M. Yazid Abu , M.G. Gençyilmaz
Hybrid flow shop environment generally refers to the flow shop with multiple parallel machines per stage. Hybrid flow shop scheduling problem (HFSP) is a complex combinatorial optimization problem that came across in many real-life problems. In this study a real-life HFSP of a lubricant company is considered where the aim is to minimize total weighted completion time of the jobs. Apart from classical HFSPs the studied problem has additional constraints such as machine eligibility sequence-dependent setup times and machine capacities. Due to the additional constraints in the system a novel mixed integer linear programming model is proposed for the studied HFSP with three stages. As the problem is NP-hard two constructive heuristic algorithms and an improvement heuristic algorithm are also developed. The performance of the proposed heuristic algorithms is evaluated by comparisons with the optimal results obtained from the mathematical model. The extensive computational results show that proposed heuristic algorithms find near optimal results in reasonable computational times. Sensitivity analysis is also performed for the weight parameter of the problem which indicates that the proposed heuristic algorithms also perform very well for different weight parameter values. Finally the proposed heuristic algorithms are integrated into a user-friendly decision support system using Microsoft Excel VBA interface to provide an efficient scheduling tool for the company. © 2022 Elsevier B.V. All rights reserved.
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 Lost Sales Make-to-Stock System with Batch Demand and Batch Production
(Springer Science and Business Media Deutschland GmbH, 2024) Sinem Özkan; Mert Yandımata; Önder Bulut; Yandımata, Mert; Özkan, Sinem; Bulut, Önder; N.M. Durakbasa , M.G. Gençyılmaz
This study considers a production setting of a single item single production resource make-to-stock production system with batch demand batch production and lost sales. Demand arrives as a Poisson process with a randomly distributed batch size. It is assumed that the batch demand can be partially satisfied and unsatisfied demands are lost. Production time follows an exponential distribution and each production order contains a single lot that does not exceed the maximum lot size. The decision to be considered in managing such a system is the production control decision which determines when to start production and how much to produce in a batch. This study contributes to the technical literature on controlling make-to-stock systems by addressing a single production resource simultaneously with batch demand and batch production. The system is formulated with the dynamic programming and the model is solved using the value iteration algorithm. In the light of the results obtained by using this algorithm it has been shown by numerical studies that the optimal production policy is a dynamic policy. © 2024 Elsevier B.V. All rights reserved.
A Multi-objective Approach to Flight Scheduling and Fleet Assignment in Hub Network
(Springer, 2025) Melis Tan Tacoglu; Mustafa Arslan Ornek; Cemalettin Öztürk; Ornek, Mustafa Arslan; Ozturk, Cemalettin; Tacoglu, Melis Tan
The hub-and-spoke (HS) network is a widely used business strategy by airlines to optimize their operations and increase their reach by connecting multiple destinations through a central hub and the majority of the passengers are transit passengers. The airline schedule planning process starts with the flight scheduling problem (FSP) to generate a timetable in advance of six months. Then the fleet assignment problem (FAP) is examined to determine aircraft types. This sequential solution approach causes suboptimal solutions and the schedule must be adjusted to increased demand. Due to the complexity of this problem this study focuses specifically on incremental schedule design with one hub two-flight leg network. This study presents a Multi-Objective Mixed Integer Programming Model for integrated FSP and FAP to adjust the generated timetable with launching new flights. Two solution approaches are proposed to decide the new proposed flight’s time aircraft type and passenger assignment: the Weighted Goal Programming Model (WGPM) and the Lexicographic Goal Programming Model (LGPM). This study shows that there is a conflicting relationship between cost and C02 emissions in the flight scheduling process. If carbon dioxide emissions are prioritized airlines need to schedule more flights with small-capacity aircraft. © 2025 Elsevier B.V. All rights reserved.
A Multi-sided and Multi-model Assembly Line Balancing Problem
(Springer Science and Business Media Deutschland GmbH, 2020-10-26) Seda Gemici; Emine Otuzbir; İrem Almila Koçyiğit; Sinem Pekelli; Fethi Tüzmen; Hande Oztop; Levent Kandiller; Pekelli, Sinem; Otuzbir, Emine; Gemici, Seda; Koçyiğit, İrem Almila; Tüzmen, Fethi; Öztop, Hande; Kandiller, Levent; N.M. Durakbasa , M.G. Gençyılmaz
In this paper we study a real-life assembly line balancing problem (ALBP) of a cooler manufacturer brand in Manisa Turkey. The aim of this study is to create an effective assembly line balancing tool for the company which minimizes the number of stations and balances the total workloads of the stations while keeping the number of products produced the same. The studied ALBP is Type-1 ALBP that minimizes the number of workstations given a cycle time which is determined by a bottleneck operation. However different from the standard Type-1 ALBP some of the stations are two-sided stations in the studied assembly line. There are special constraints in the studied ALBP such as concurrent tasks preemptive tasks zone-restricted tasks and parallel tasks. Due to these additional characteristics of the system a novel mixed-integer linear programming (MILP) model is proposed for the studied ALBP to minimize the number of workstations. A secondary objective which balances the workload of the stations is also considered in the proposed MILP model using a lexicographic optimization. The computational experiments show that the proposed MILP model can obtain the optimal solution in reasonable computational time. When the model results are compared with the current system there is a 44% improvement in the number of stations on average. Furthermore a sensitivity analysis is performed to analyze the trade-off between the number of stations and cycle time criteria employing an ε-constraint method. Finally a user-friendly DSS is developed by embedding the proposed MILP model. © 2020 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
A New Heuristic for PCBs Grouping Problem with Setup Times
(IEEE Computer Society help@computer.org, 2020-07) Jiangping Huang; Quanke Pan; M. Fatih Tasgetiren; Yingying Huang; Tasgetiren, M Fatih; Huang, Ying-Ying; Pan, Quan-Ke; Huang, Jiang-Ping; J. Fu , J. Sun
In this paper we present a new heuristic to divide a batch of printed circuit boards (PCBs) into subgroups to save the setup time for loading and unloading components from the assembly machine. In the heuristic we propose several concepts about similarity to make the number of groups as few as possible. To better show the relationship between the PCB types and the component types of a group we introduce a new solution representation. In addition considering the characteristics of the PCBs grouping problem (PGP) a method for pairing PCBs is presented. With the PCB pairs an iterative scheme is applied to start a new group. We try the rest PCBs one by one according to the similarity between it and the PCB group. Finally the experiments and comparisons show the good performance of the proposed heuristic. © 2020 Elsevier B.V. All rights reserved.
Citation - Scopus: 2
A Parallel Machine Scheduling Problem for a Plastic Injection Company
(Springer Science and Business Media Deutschland GmbH, 2020-10-26) 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. Gençyılmaz
In 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.
A proposed model for candidate selection process in political parties based on fuzzy logic methodology
(Association for Scientific Research membranes@mdpi.com, 2012-08-01) Yılmaz Gökşen; Onur Doǧan; Mete Eminaǧaoǧlu
Classical logic and classical set theorems are not sufficient enough when it is necessary to deal with complex decision making problems which also involve human experiences. Some researches suggest that senior management usually makes intuitive decisions in the process of selecting the candidates in political parties which brings out the need to derive a new efficient robust and applicable method. In this study the qualitative characteristics and their significance level which could be used for the candidate selection process in political parties are determined. The candidate selection process consisting vague inputs is analyzed by fuzzy logic methodology and a quantitative final score has been determined for the candidate. It has been shown that the model provided some realistic and promising results which could enable further studies to derive more optimized and enhanced models for similar purposes. © 2020 Elsevier B.V. All rights reserved.
A qualitative exploration of user perceptions and expectations of raw milk vending machines
(Inderscience Publishers, 2023) Selen Devrim Ülkebaş; Ezgi Ozan Avci; Ülkebaş, Selen Devrim; Avcı, Ezgi Ozan
Fresh food vending machines (VMs) can be an alternative channel for sustainable and health-conscious retailing. However VMs that dispense fresh items such as raw milk pose distinct challenges in user interaction. This study explores user perceptions and expectations regarding the anticipated use of raw milk vending machines (RM-VMs). The study incorporates both exploratory and evaluative inquiry through the use of in-depth interviews supplemented with visual prompts. The study highlighted the critical importance of food hygiene mostly attributed to human errors. Key user expectations for enhancing food safety and user interaction in the next generation of RM-VMs emerged as digital technology integration and automation of tasks with the aim of improving the discoverability and understandability of product features minimising human errors in use enhancing information quality and quantity adapting to evolving shopping practices and diverse user profiles and elevating service quality. © 2024 Elsevier B.V. All rights reserved.
Citation - Scopus: 1
A Simulation Based Analysis for Sewing Lines of Apparel Industry
(Springer Science and Business Media Deutschland GmbH, 2023) Berk Kaya; Zeynep Hazal Soyan; Işılay Aydın; Sanemnaz Yurteri; Zilan Gerilakan; Önder Bulut; Burak Özdeş; Can Elhan; Zeynep Rala; Şafak Birol; Birol, Şafak; Yurteri, Sanemnaz; Kaya, Berk; Aydın, Işılay; Bulut, Önder; Gerilakan, Zilan; Soyan, Zeynep Hazal; N.M. Durakbasa , M.G. Gençyılmaz
One of the frequently encountered problems in the labour-intensive apparel industry is the deviation from the target deadlines. The biggest observed reason for this problem is that the standard operation times and therefore production targets are being defined as deterministic values in the stochastic environment. The statistical studies carried out in this project show that the standard deviation of the operation times is too significant to be ignored. The natural randomness in the performance of the workers and additional factors such as fatigue and learning effect are some of the most important reasons that increase the variability in the system. The project is carried out in conjunction with one of Turkey’s top companies within the apparel sector TYH Tekstil A.Ş. Different policies are applied by the company to dynamically solve the problems encountered during production. In the literature review different simulation-based policy methods for a sample order were examined. However since the company’s sewing line has its unique characteristics the reviewed policies alone were determined not to be suitable for use. This project aims to determine the mentioned randomness parameters by analyzing the day-hour variability of the operation times statistically and provide the company with a tool that will simulate the sewing lines ahead of production using the order-specific inputs and data analysis dynamically analyze and improve the performance of the sewing lines by Tabu search algorithm and visually/verbally report any problematic operations/occasions that may arise and performance improvements made by the decision policies for minimizing deviations from target deadlines. To increase the flexibility of the system and make it dynamic the Python programming language was used. © 2023 Elsevier B.V. All rights reserved.
A Single Machine Job Scheduling Problem with Sequence Dependent Setup Times
(Springer Science and Business Media Deutschland GmbH, 2020-10-26) Aylin Elibol; Selen Tosun; Emin Erbay; Egemen Orta; Öykü Gökşen; Asena Ceritoğlu; Çınar Arabacı; Hande Oztop; Mustafa Arslan Ornek; Ceritoğlu, Asena; Erbay, Emin; Örnek, Mustafa Arslan; Elibol, Aylin; Gökşen, Öykü; Tosun, Selen; Orta, Egemen; N.M. Durakbasa , M.G. Gençyılmaz
In this paper a real-life single machine job scheduling problem with sequence-dependent setup times of a hood manufacturer company is addressed to minimize total weighted tardiness of the jobs with given due dates. Initially a mixed-integer linear programming model is developed for the problem. Since the problem is NP-hard heuristic algorithms are also proposed to solve larger instances. Namely Apparent Tardiness Cost with Setups (ATCS) Earliest Due Date (EDD) Weighted Earliest Due Dates (WEDD) Shortest Processing Time (SPT) and Weighted Shortest Processing Time (WSPT) rule-based algorithms are developed for the problem. A swap move-based improvement is also employed in the proposed heuristic algorithms. To evaluate the effectiveness and efficiency of the proposed solution approaches a comprehensive computational study is conducted by developing instances for the problem using the methodology from the related literature. Initially optimal results are obtained for small instances by solving the mathematical model. Then the performance of the proposed heuristic algorithms is evaluated by comparisons with the optimal results and time-limited model results. The computational results show that proposed ATCS rule-based heuristic is very effective to solve the problem. A user-friendly decision support system (DSS) is also developed to serve users with easy and efficient job scheduling. © 2020 Elsevier B.V. All rights reserved.

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