İşletme Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/411

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BULANIK ÇOK KRİTERLİ KARAR VERME ORTAMINDA YEŞİL TEDARİKÇİ SEÇİMİ
(ACC Publishing, 2019) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
Yasal düzenlemeler ve müşterilerin artan çevre koruma bilinci, işletmeleri tedarik zinciri faaliyetlerini,yeşil tedarikçi zinciri yönetimine uygun olarak çevreye daha az zarar verecek şekilde yapılandırmaya özengösterir hale getirmiştir. Yeşil tedarikçi seçimi, yeşil tedarik zinciri yönetiminde rol alan önemli faktörlerdendir.Yeşil tedarikçi seçiminde ekonomik ve çevresel kriterler birlikte ele alınmaktadır. Yeşil tedarikçi seçimproblemleri belirsizlik içerdiğinden karar vericilerin dilsel ifadelerle görüşlerini belirtebilecekleri bulanık kümeteorisi kullanılmaktadır. Yeşil tedarikçi seçim probleminde, birden fazla alternatif birden fazla kritere göredeğerlendirildiğinden, çok kriterli karar verme yöntemleri bu problemin çözümü için oldukça uygundur. Buçalışmanın temel amacı, nicel verilerin yetersiz olduğu yeşil tedarikçi seçim ortamında, önerilen çözümyöntemini kullanarak yeşil tedarikçi seçimini gerçekleştirmektir. Önerilen modelde, yeşil tedarikçi sıralamasıBulanık TOPSİS, Bulanık Vikor, Bulanık Gri İlişkisel Analiz, Bulanık Aras yöntemleri ile elde edilmiştir.Tedarikçi seçim ve değerlendirme kriter ağırlıkları bulanık SWARA yöntemiyle belirlenmiş ve bilgi kaybınınolmasını önlemek için çok kriterli karar verme problemlerinde de kriter ağırlıkları bulanık sayı olarakkullanılmıştır. Önerilen çözüm modeli, orta ölçekli şehir mobilya üretimi gerçekleştiren bir işletmenin yeşiltedarikçi seçim sürecine uygulanmıştır. Bu uygulama için yapılan hesaplamalar neticesinde dört yöntemden aynıtedarikçi sıralaması elde edilmiştir. Çalışmada kullanılan dört çok kriterli karar verme yönteminin temel vekavramsal özellikleri değerlendirilmiştir. Bu problem için gri ilişkisel analiz yönteminin daha uygun olduğusonucuna varılmıştır.
Greedy randomized adaptive search for dynamic flexible job-shop scheduling
(ELSEVIER SCI LTD, THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2020) Baykasoglu, Adil; Madenoglu, Fatma S.; Hamzadayi, Alper; 0000-0002-5577-4471; 0000-0002-4952-7239; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü
Dynamic flexible job shop scheduling problem is studied under the events such as new order arrivals, changes in due dates, machine breakdowns, order cancellations, and appearance of urgent orders. This paper presents a constructive algorithm which can solve FJSP and DFJSP with machine capacity constraints and sequence-dependent setup times, and employs greedy randomized adaptive search procedure (GRASP). Besides, Order Review Release (ORR) mechanism and order acceptance/rejection decisions are also incorporated into the proposed method in order to adjust capacity execution considering customer due date requirements. The lexicographic method is utilized to assess the objectives: schedule instability, makespan, mean tardiness and mean flow time. A group of experiments is also carried out in order to verify the suitability of the GRASP in solving the flexible job shop scheduling problem. Benchmark problems are formed for different problem scales with dynamic events. The event-driven rescheduling strategy is also compared with periodical rescheduling strategy. Results of the extensive computational experiment presents that proposed approach is very effective and can provide reasonable schedules under event-driven and periodic scheduling scenarios.
Green vehicle routing problem
(Nova Science Publishers, Inc., 2024) Madenoglu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoglu, Fatma Selen
The decrease in natural resources, the fact that greenhouse gases cause global warming, and consumers' sensitivity to environmental, and health issues have forced businesses to develop sustainable strategies. The idea of "green logistics," which is focused on carrying out economically sensible environmental activities when producing goods and services, has gained significant relevance for this reason. Transportation activity is one of the most basic costs of logistics activity. Due to the fuels used in transportation and the greenhouse gases released, it has become vital to develop and implement sustainable and green energy policies in logistics activities. Green logistics has become one of the areas that needs to be emphasized. A metaheuristic is presented and proposed to solve the vehicle routing problem, which is a type of vehicle routing problem involved in optimizing simultaneous pickup and delivery considering carbon emissions in logistics activities. A green logistics approach is presented in order to guide businesses that aim to produce services in accordance with sustainable and green energy policies.
A GROUP DECISION-MAKING METHOD FOR RANKING PROBLEMS UNDER SUSTAINABILITY, RISKS, AND INTUITIONISTIC FUZZY ENVIRONMENT
(Pamukkale Üniversitesi, 2023) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
This paper presents a group decision-making mechanism to properly manage ranking problems in an intuitionistic fuzzy environment. TOPSIS ranking multi-criteria decision-making (MCDM) methods is utilized under the intuitionistic fuzzy set theory. This solution technique examines the sets of criteria employed in decision-making problems, the preferences of a group of decision-makers, and the importance levels of decision-makers. Managers use the ranking methods as a reliable technique for making supplier evaluation decisions. Furthermore, the supply chain suffers from the shortage of materials, transportation problems, etc. In the post COVID-19 era, the need for a practical and exhaustive tool is explicit. An illustrative case on a supplier selection problem considering sustainability and risks in the post-COVID-19 era is used to demonstrate the applicability of the proposed technique by detailing the procedure step by step. A comparative analysis of the results is carried out. The results are compared with the results of the MARCOS method. The results show that the presented methodology is applicable to the other areas as well.
HİBRİT AKIŞ TİPİ ÇİZELGELEME PROBLEMİNİN PARÇACIK SÜRÜ OPTİMİZASYON ALGORİTMASIYLA ÇÖZÜMÜNE BAŞLANGIÇ POPÜLASYONUN ETKİSİ
(Marmara Üniversitesi, 2020) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
Bu çalışmada, birden fazla aşama, her aşamada özdeş paralel makineler ve makinelerde işlenen işler arası geçişlerde sıraya bağlı hazırlık süresini içeren hibrit akış tipi çizelgeleme problemi sunulmuştur. Metasezgisel yöntemler bu karmaşık problemlerin çözümünde tercih edilmektedir. Metasezgisel yöntemlerde optimum çözüm ararken, oluşturulan başlangıç çözümlerin nihai sonuca etkisi oldukça önemlidir. Hibrit akış tipi çizelgeleme probleminin çözümüne önerilen parçacık sürü optimizasyon (PSO) algoritmasına farklı başlangıç çözüm oluşturma yöntemlerinin etkisi incelenmiştir. Dört farklı başlangıç çözüm oluşturma yaklaşımı sonuçları karşılaştırılmıştır. Nawaz, Enscore, Ham (NEH) sezgiselinin diğer yöntemlerden daha etkili olduğu sonucuna ulaşılmıştır.
Industry 4.0: A bibliometric analysis
(Nova Science Publishers, Inc., 2023) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
With the emergence of Industry 4.0, organizations' interest in digital transformation has significantly expanded to remain competitive. As a result, organizational digital transformations have appeared. Nowadays, machine learning is built into every device, and automation has taken center stage. This paper presents a bibliometric study and in-depth research on the most recent advancements in the "Industry 4.0" field. The top 10 most cited publications and authors, main research areas, publications, and countries are all examined as part of the bibliometric study, which also extracts data on the overall number of publications and citations. The organizational transformation highlighted in the publications is then examined after a detailed analysis of the most cited publications. In this paper, the publications on Industry 4.0 are examined and in addition, publications that deal with Industry 4.0 and organizational transformation are presented.
Managing transportation in supply chain: Metaheuristics for solving a capacitated fixed-charge transportation problem
(IGI Global, 2021) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
Supply chain management is the managing of all processes of goods, services, and information from suppliers to customers. Transportation network design is an important part of effective supply chain management. This chapter presents the two-stage fixed-charge transportation problem in a supply chain to minimize the total cost containing the opening cost of distribution centers, transportation cost from manufacture to distribution centers and from distribution centers to customers, and fixed cost for transportation from distribution centers to customers. There are the capacity constraints on distribution centers in order to consider real life situations in this chapter. A constructive based algorithm and a population-based algorithm are proposed to solve this complex optimization problem. Taguchi experimental design is applied for determining the best combinations of parameters. The experimental studies are conducted to compare the performance of the proposed algorithms according to solution quality.
PERFORMANCE EVALUATION OF ENERGY COMPANIES WITH A NOVEL INTEGRATED MULTI-CRITERIA DECISION MAKING METHOD
(Kafkas Üniversitesi, 2022) Madenoğlu, Fatma Selen; Ünlüsoy, Ömer Faruk; Yılmaz, Çağatay; 0000-0002-5577-4471; 0000-0002-3252-5720; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen; Ünlüsoy, Ömer Faruk
Financial statements are an important tool for assessing and analyzing an organization's financial performance. Financial performance analysis allows for an accurate and appropriate appraisal of an organization's performance. The evaluation procedure must be thoroughly stated because financial performance indicators represent a company's competitiveness. This study provides a novel integrated multi-criteria decision-making method for analyzing an organization's financial performance. The applicability of the proposed method is assessed employing financial ratios that are integrated to generate a financial performance score for eight well-known Turkish energy companies. The criteria are weighted using the entropy method in the proposed method. The multiattributive border approximation area comparison (MABAC) method is used to rank the companies. As the weights of the criteria have an impact on the ranking outcomes, a sensitivity analysis of the weights is performed. We also exhibit a comparison analysis of energy company rankings to validate the proposed approach's results using four MCDM methods: ELECTRE, MAUT, TOPSIS, and WASPAS. In addition, an alternative weighting method is also used to evaluate the results. The results show that the proposed method is an effective MCDM for coping with evaluation problems
Portfolio optimization: An application on the BIST-30 Index
(Peter Lang AG, 2023) Madenoğlu, Fatma Selen; Ünlüsoy, Ömer Faruk; 0000-0002-5577-4471; 0000-0002-3252-5720; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen; Ünlüsoy, Ömer Faruk
F. S. Madenoğlu And Ö. F. Ünlüsoy, "Portfolio Optimization: An Application on the BIST-30 Index," In Interdisciplinary Public Finance, Business and Economics Studies– Volume VI , Berlin: Peter Lang Publishing, Inc., 2023, pp.75-87.
Solving Optimization Problem with Particle Swarm Optimization: Solving Hybrid Flow Shop Scheduling Problem with Particle Swarm Optimization Algorithm
(SPRINGER LINK, 2021) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
The flow shop scheduling problem is widely discussed in the literature since it is frequently applied in real industry. This paper presents a variant of flow shop scheduling problem with parallel machines. The proposed problem includes multistage and identical parallel machines at each stage, and the sequence-dependent setup time and transportation time are considered. The objective function is minimization of makespan. The particle swarm optimization algorithm (PSO) is addressed to solve the problem and compared with genetic algorithm and heuristics. The benchmark instances are generated to demonstrate the performance of the PSO. The numerical results show that the PSO significantly outperforms the comparison set.
SOLVING THE HYBRID FLOW SHOP SCHEDULING PROBLEM USING HEURISTIC ALGORITHMS
(ACC Publishing, 2019) Madenoğlu, Fatma Selen; 0000-0002-5577-4471; AGÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü; Madenoğlu, Fatma Selen
A variant of the hybrid flow shop (HFS) problem considering missing operations, transportation timesand sequence-dependent setup times is investigated. Heuristic algorithms along with dispatching rulesanddispatching rules are used to solve the given problem. The objective function is minimization makespan. Thecomputational experimets are conducted to test the performance of the heuristic algoirthms and dispatching rules.In order to depict the effect of the factors: number of jobs, number of machines, number of production stages, levelof missing operations on the result, the additiol experimentes are carried out. The result of NEH heuristic withSPTF rule outperformed other heuristics for the proposed HFS problems.

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