WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11289

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Citation - WoS: 9
Citation - Scopus: 9
2-D and 3-D basin site effects in Izmir-Bayrakli during the October 30- 2020 Mw7.0 Samos earthquake
(SPRINGER, 2023-07-11) Kemal Onder Cetin; Moutasem Zarzour; Elife Cakir; S. Caglar Tuna; Selim Altun; Altun, Selim; Zarzour, Moutasem; Cetin, Kemal Onder; Cakir, Elife; Tuna, S. Caglar
During the October 30 2020 M(w)7.0 Samos Earthquake the Turkiye-Izmir-Bayrakli district was affected the most due to the geometry and the deep-soft alluvial nature of the basin although the district is approximately 70 km away from the epicenter. In this study the seismic response of the Bayrakli basin and the role of the soil stratigraphy and basin geometry on the recorded amplifications and prolonging of seismic shakings are investigated by using 1- 2-and 3-D non-linear finite element-based dynamic response analyses. The assessment results are presented in the form of spectral amplification ratios A(T). The highest A(T) values were estimated at spectral periods T = 0.85 and 1 s. They exceed five in both the east-west and the north-south directions more pronounced in the latter one. A(T) was decomposed into the product of two independent amplification factors namely rock to soil amplifications A(Soil)(T) and 1-D soil column to 3-D soil basin amplifications A(Basin)(T). A(Basin)(T) values for T = 0.85 and 1 s are estimated as high as 1.4 and 1.6 in the east-west and the north-south directions respectively. These values suggest that the 3-D geometry of the Bayrakli basin amplifies the spectral accelerations by 40-60% at T = 0.85 and 1 s. The unique combination of a deep-soft alluvial site with 3-D basin geometry and overlying 7-9 story residential buildings consistently favors and amplifies the seismic energy in the spectral period range of 0.7-1.0 s. This multi-fold increased seismic demand combined with poor structural design and construction details lead to localized structural damage and over 117 life losses.
Citation - WoS: 18
Citation - Scopus: 22
A bi-objective mathematical model for product allocation in block stacking warehouses
(WILEY, 2018-01-09) Omer Ozturkoglu; Ozturkoglu, Omer
Put-away and picking operations in warehouses play a critical role in determining operating costs and customer response time. While the place where products are put away has an important effect on picking efficiency due to accessibility it also affects space usage which is critical for space availability and space costs. Hence this study focuses on put-away operations in pallet-in pallet-out block stacking warehouses. We develop a unique bi-objective mathematical model and a constructive heuristic algorithm to allocate products to storage lanes while considering two objectives simultaneously: minimizing total travel distance and maximizing average storage usage. We test our model and heuristic through a real company case study and randomly generated large-sized problem instances. We show that the model and heuristic offer better storage usage with reduced travel distance than the company's approach when the two objectives have equal weight. We also present a set of nondominated solutions for each problem instance. We present that the heuristic seems beneficial for the warehouse industry due to its short run time and effective solutions.
A big data analytics based methodology for strategic decision making
(Emerald Group Holdings Ltd., 2020-05-26) Murat Özemre; Ozgur Kabadurmus
Purpose: The purpose of this paper is to present a novel framework for strategic decision making using Big Data Analytics (BDA) methodology. Design/methodology/approach: In this study two different machine learning algorithms Random Forest (RF) and Artificial Neural Networks (ANN) are employed to forecast export volumes using an extensive amount of open trade data. The forecasted values are included in the Boston Consulting Group (BCG) Matrix to conduct strategic market analysis. Findings: The proposed methodology is validated using a hypothetical case study of a Chinese company exporting refrigerators and freezers. The results show that the proposed methodology makes accurate trade forecasts and helps to conduct strategic market analysis effectively. Also the RF performs better than the ANN in terms of forecast accuracy. Research limitations/implications: This study presents only one case study to test the proposed methodology. In future studies the validity of the proposed method can be further generalized in different product groups and countries. Practical implications: In today’s highly competitive business environment an effective strategic market analysis requires importers or exporters to make better predictions and strategic decisions. Using the proposed BDA based methodology companies can effectively identify new business opportunities and adjust their strategic decisions accordingly. Originality/value: This is the first study to present a holistic methodology for strategic market analysis using BDA. The proposed methodology accurately forecasts international trade volumes and facilitates the strategic decision-making process by providing future insights into global markets. © 2021 Elsevier B.V. All rights reserved.
A circular business cluster model for sustainable operations management
(Taylor and Francis Ltd., 2021-11-25) Erhan Ada; Muhittin Saǧnak; Sachin Kumar Kumar Mangla; Yigit Kazancoglu
Ecological pollution scarcity of resources climate change and population growth have forced organisations to transform from a linear to a circular economy. Hence the need arises to redesign value chains and traditional business models. Thus the aim of this study is to develop a new conceptual eco-cluster model called ‘Circular Business Cluster Model’ to combine the advantages of both clustering and a circular economy. This paper seeks to establish a framework and provide guidelines for policy-makers such as governments local authorities and organised industrial zone administrators. The contribution of this paper is to highlight and emphasise the crucial role of circular economy principles to transform a classical business model into an eco-business model. Circular Business Cluster Model includes the conceptual framework network structure interactions between cluster components and 6R activities. A case study was conducted to check the applicability of the proposed Circular Business Cluster Model. Eleven centres in this model were evaluated. Fuzzy Best-Worst Method (BWM) was used to find the relative weights. Based on the Circular Business Cluster Model theoretical and managerial implications have been presented. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 36
Citation - Scopus: 26
A circular food supply chain network model to reduce food waste
(Springer, 2022-05-09) Ozgur Kabadurmus; Yigit Kazancoglu; Damla Yüksel; Melisa Ozbiltekin-Pala; Yüksel, Damla; Pala, Melisa Özbiltekin; Kabadurmus, Ozgur; Kazançoğlu, Yiğit
Food loss and waste (FLW) is a growing global problem throughout the world. The rapid increase in food waste and deficiencies in treatment processes have led to greater harm to the environment. A circular food supply chain (FSC) is now an essential means of encouraging circular economy. Proper food waste treatment and recycling operations can not only benefit the environment but these wastes can also be used as raw material for production in a circular economy. In this study a circular food supply chain network model is designed to reduce the food waste generated in the circular food supply chain systems of municipalities. Then a mixed-integer linear programming model is generated to model the proposed circular food supply chain network model. The MILP model is a network model aimed at reducing the food waste generated. To do so two objectives are considered: the overall cost of the network is minimized and the amount of distributed food waste from the generation nodes to the end nodes is maximized. Due to the bi-objective nature of the proposed mathematical model the Improved Augmented Epsilon Constraint method (AUGMECON2) is implemented to solve the problem optimally. To illustrate the applicability and effectiveness of the proposed mathematical model two real-life case studies were carried out in Izmir the third largest city in Turkey. The computational results demonstrate that the proposed model is beneficial for both small and large municipalities since it provides the Pareto-optimal set where the total amount of distributed food waste is maximized and the total cost is minimized. © 2022 Elsevier B.V. All rights reserved.
A collaborative numerical simulation-soft computing approach for earth dams first impoundment modeling
(Elsevier Ltd, 2023-12) Behzad Shakouri; Mirali Mohammadi; Mir Jafar Sadegh Safari; Mohammad Amin Hariri-Ardebili
Uncertainty quantification plays a crucial role in the design monitoring and risk assessment of earth dams. To reduce the computational burden we employ a combination of finite difference method and soft computing techniques to investigate material uncertainties in earth dams during the initial impoundment stage. The findings of sensitivity analysis with the Tornado diagram indicate that key material properties such as dry density elasticity modulus friction angle and Poisson's ratio significantly influence the displacements and stress analysis. In our study we explore four variants of extreme learning machines (ELMs): the standalone ELM hybridized versions with the improved grey wolf optimizer algorithm ant colony optimization for continuous domains and artificial bee colony. These methods are assessed across various training sizes to predict multiple parameters including horizontal and vertical displacements stresses and the factor of safety (FoS). The hybridized ELM with the improved grey wolf optimizer algorithm emerges as the superior choice for most of the response variables. A minimum of 200 numerical simulations is required to establish a stable and accurate meta-model with an average prediction error of less than 3% for responses and the FoS. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 12
Citation - Scopus: 13
A comparative study on estimating the landfill gas potential: Modeling and analysis
(Taylor and Francis Inc. 325 Chestnut St Suite 800 Philadelphia PA 19106, 2016-08-12) Ali Kemal Çakir; Huseyin Gunerhan; A. Hepbasli; Hepbasli, A.; Gunerhan, H.; Cakir, A. K.
The main objective of this study is to investigate the use of the landfill gas as potential energy and electricity obtained from the municipal solid waste (domestic industrial medical waste and sewage sludge) stored regularly in the Harmandali solid waste landfill area within the boundaries of the contiguous area of Izmir. The most important factor in making a decision about energy potential in the landfill is the amount of methane in the landfill gas. There are several approaches that have been used to determine the amount of the landfill gas. In this study three different methods and one approach in the literature were used for this purpose. The methods used are the Multi-Phase the LandGEM and the IPCC 2006. The results of the landfill gas obtained using the three methods namely the Multi-Phase the LandGEM (k = 0.35 k = 0.1 and k = 0.05) and the IPCC 2006 were as follows respectively: 291897215 792073359 769734749 681685027 and 491752247 m3. It may be concluded that the Harmandali Landfill has high landfill gas potential based on the measurements and mathematical methods used in the Harmandali landfill. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 4
A Comprehensive Analysis of Data Augmentation Methods for Speech Emotion Recognition
(Institute of Electrical and Electronics Engineers Inc., 2025) Umut Avci; Avci, Umut
The limited availability of labeled emotional speech data remains a significant challenge in the development of robust speech emotion recognition systems. This paper presents a comprehensive investigation of the effectiveness of diverse data augmentation strategies for enhancing emotion recognition performance. Three different data augmentation categories were examined: audio-based transformations image-based modifications and feature-level synthesis. Seventeen transformations were used in audio-based data augmentation to change the time and frequency content of the raw audio signal. Eight transformations such as shifting rotating and zooming were applied to the spectrogram images for image-based data augmentation. The SpecAugment method was also used to transform the spectrograms into versions with masked time and frequency axes. In feature-space-based approaches new feature vectors were generated using five oversampling algorithms and a generative adversarial network. Experimental results from the EMO-DB and IEMOCAP datasets demonstrate that the data augmentation approaches enhance emotion classification performance by up to six percent. Empirical evidence indicates that training sets augmented through combinations of audio-based transformations yield the highest performance gains. In contrast the GAN-based approach fails to improve the classification performance. © 2025 Elsevier B.V. All rights reserved.
A conceptual framework for a new service model: digital servitization with an Industrial 4.0 perspective
(Emerald Publishing, 2023-11-14) Tilbe Adsız; Yucel Yilmaz Ozturkoglu
Purpose: Recently increasing costs and competitive pressure have accelerated the search for different business models in both the production and service sectors. The rapid development of technology has increased the importance of digitalization especially in developing new and different strategies. The digital service business model has also become a new business model that companies have recently preferred. In addition to its many advantages it is a business model in which different barriers arise in practice. When we look at the literature there are very few studies especially on digital servitization. The purpose of this study is to integrate the concept of digital servitization with the Industry 4.0 perspective. Design/methodology/approach: To achieve this aim first the authors identify various challenges and barriers in front of digital servitization based on the Industry 4.0 perspective. Later they determine the relative importance of these barriers critical to the success of digital servitization. Lastly one multi-criteria decision-making method the fuzzy decision-making trial and evaluation laboratory method is used to analyze the cause-and-effect relationship between each barrier based on the Industry 4.0 perspective Findings: Based on the results the most crucial cause-and-effect barriers are insufficient infrastructure/lack of IT infrastructure and high implementation respectively. Therefore this study offers the reader the possible barriers to sustainable digital servitization with Industry 4.0 perspective implementations and comprehensive solutions for these barriers. In addition this study draws a roadmap for disseminating digital service applications. Originality/value: There is no study to the best of the authors’ knowledge about determining barriers and problems with merging digital servitization with the Industry 4.0 perspective. So there is still a significant gap in the literature about investigating these two essential topics from the Industry 4.0 perspective. © 2025 Elsevier B.V. All rights reserved.
Citation - WoS: 171
Citation - Scopus: 201
A conceptual framework for barriers of circular supply chains for sustainability in the textile industry
(WILEY, 2020-07-22) Ipek Kazancoglu; Yigit Kazancoglu; Emel Yarimoglu; Aysun Kahraman; Yarimoglu, Emel; Kazancoglu, Ipek; Kazancoglu, Yigit; Kahraman, Aysun
Circular economy is a contemporary concept including usage of renewable materials and technologies. The transition to the circular economy creates value through closed-loop systems reverse logistics eco-design product life cycle management and clean production. The aim of the study was to propose a holistic conceptual framework for barriers of circular supply chain for sustainability in the textile industry. Within this aim an in-depth literature review on barriers was conducted by covering all supply chain stages and circular initiatives in textile industry. Then a focus group study was implemented. In the focus group study barriers related to supply chains that prevent companies to implement the circular economy were discussed and validated. As a result a total of 25 barriers were classified under nine main categories such as (a) management and decision-making (b) labour (c) design challenges (d) materials (e) rules and regulations (f) lack of knowledge and awareness (g) lack of integration and collaboration (h) cost and (i) technical infrastructure.
Citation - WoS: 102
Citation - Scopus: 147
A conceptual framework for blockchain-based sustainable supply chain and evaluating implementation barriers: A case of the tea supply chain
(WILEY, 2022-03-23) Sachin Kumar Mangla; Yigit Kazancoglu; Abdullah Yildizbasi; Cihat Ozturk; Ahmet Calik; Calik, Ahmet; Yildizbasi, Abdullah; Ozturk, Cihat; Mangla, Sachin Kumar; Kazancoglu, Yigit
The increasing population and income inequality in the last decades have made it necessary to focus on the concept of sustainability. In the changing world order with economic crises instabilities pandemics and social media sustainability awareness differs significantly from past years. In addition developing new technologies and concepts (big data blockchain IoT robotic etc.) plays a crucial role in meeting social awareness in terms of sustainability. Food sustainability is also one of the most important pillars in this concept. The integration of new technologies in agriculture and food chains will enable the current world population to use resources more efficiently and sustainably. Blockchain one of the technologies that emerged with the arrival of Industry 4.0 is a technology that can be used effectively in many sectors. Particularly in supply chain networks it is seen as a technology that supports the sustainability concept due to its features such as decentralization reliability transparency consensus standards and traceability. However since blockchain is an immature and new technology there are some challenges with integrating it into existing conventional systems. This study aims to present a conceptual framework for the integration of blockchain technology to establish a sustainable tea supply chain define possible actions and prioritize the possible risks that may arise in this integration process, this will be done through the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) approach. In this context initially the current tea supply chain will be considered and the activities carried out will be defined in terms of technological environmental and strategic sustainability. Then the design that includes the integration of all activities with blockchain technology is presented. The proposed design covers the entire tea supply chain from end to end and is considered with regard to all sustainability dimensions. In the proposed framework barriers that may be encountered and risks that may arise at each stage of the tea supply chain process are identified, managerial implications are then presented to eliminate these risks. To enhance the use of the recommendations made risks and barriers are prioritized with SF-AHP management. Thus the problems that need to be solved primarily in the technological transformation process can be evaluated more clearly. The proposed theoretical framework is expected to extend to all agricultural practices and support technological advances throughout the agricultural sector.
Citation - WoS: 3
Citation - Scopus: 5
A copula-based BRDF model
(Blackwell Publishing Ltd, 2010-09) Aydin Öztürk; Murat Kurt; Ahmet Bilgili; Kurt, Murat; Bilgili, Ahmet; Ozturk, Aydin
In this paper we introduce a novel approach for modeling surface reflection. We focus on using a family of probability distributions called Archimedean copulas as BRDF models. The Archimedean representation has an attractive property in that the multivariate distributions are characterized by their marginal distributions through a single univariate function only. It is shown that the proposed model meets the reciprocity property of reflection. Based on measured BRDF data we demonstrate that the proposed approach provides a good approximation to BRDF. Empirical comparisons are made with some classically used BRDF models. © 2010 The Eurographics Association and Blackwell Publishing Ltd. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 47
Citation - Scopus: 52
A differential evolution algorithm for the no-idle flowshop scheduling problem with total tardiness criterion
(Taylor & Francis Ltd, 2011-08-15) M. Fatih Tasgetiren; Quanke Pan; Ponnuthurai Nagaratnam Suganthan; Tay Jin Chua; Tasgetiren, M. Fatih; Suganthan, P. N.; Jin Chua, Tay; Pan, Quan-Ke; Chua, Tay Jin
In this paper we investigate the use of a continuous algorithm for the no-idle permutation flowshop scheduling (NIPFS) problem with tardiness criterion. For this purpose a differential evolution algorithm with variable parameter search (vpsDE) is developed to be compared to a well-known random key genetic algorithm (RKGA) from the literature. The motivation is due to the fact that a continuous DE can be very competitive for the problems where RKGAs are well suited. As an application area we choose the NIPFS problem with the total tardiness criterion in which there is no literature on it to the best of our knowledge. The NIPFS problem is a variant of the well-known permutation flowshop (PFSP) scheduling problem where idle time is not allowed on machines. In other words the start time of processing the first job on a given machine must be delayed in order to satisfy the no-idle constraint. The paper presents the following contributions. First of all a continuous optimisation algorithm is used to solve a combinatorial optimisation problem where some efficient methods of converting a continuous vector to a discrete job permutation and vice versa are presented. These methods are not problem specific and can be employed in any continuous algorithm to tackle the permutation type of optimisation problems. Secondly a variable parameter search is introduced for the differential evolution algorithm which significantly accelerates the search process for global optimisation and enhances the solution quality. Thirdly some novel ways of calculating the total tardiness from makespan are introduced for the NIPFS problem. The performance of vpsDE is evaluated against a well-known RKGA from the literature. The computational results show its highly competitive performance when compared to RKGA. It is shown in this paper that the vpsDE performs better than the RKGA thus providing an alternative solution approach to the literature that the RKGA can be well suited. © 2011 Taylor & Francis. © 2011 Elsevier B.V. All rights reserved.
A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion
(2013-06) M. Fatih Tasgetiren; Quanke Pan; Ponnuthurai Nagaratnam Suganthan; Adalet Oner
In this paper we present a discrete artificial bee colony algorithm to solve the no-idle permutation flowshop scheduling problem with the total tardiness criterion. The no-idle permutation flowshop problem is a variant of the well-known permutation flowshop scheduling problem where idle time is not allowed on machines. In other words the start time of processing the first job on a given machine must be delayed in order to satisfy the no-idle constraint. The paper presents the following contributions: First of all a discrete artificial bee colony algorithm is presented to solve the problem on hand first time in the literature. Secondly some novel methods of calculating the total tardiness from makespan are introduced for the no-idle permutation flowshop scheduling problem. Finally the main contribution of the paper is due to the fact that a novel speed-up method for the insertion neighborhood is developed for the total tardiness criterion. The performance of the discrete artificial bee colony algorithm is evaluated against a traditional genetic algorithm. The computational results show its highly competitive performance when compared to the genetic algorithm. Ultimately we provide the best known solutions for the total tardiness criterion with different due date tightness levels for the first time in the literature for the Taillard's benchmark suit. © 2013 Elsevier Inc. © 2013 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 5
A Framework for Capacity Expansion Planning in Failure-Prone Flow-Networks via Systemic Risk Analysis
(Institute of Electrical and Electronics Engineers Inc., 2022-03) Nazlı Karatas Aygün; Önder Bulut; Emrah Biyik; Aygun, Nazl Karatas; Bulut, Onder; Biyik, Emrah
In this article a capacity expansion framework is proposed for failure-prone flow-networks. A systemic risk measure that quantifies the risk of unsatisfied demand due to cascaded edge failures is considered. To minimize the total cost of additional edge capacities while keeping the risk of unsatisfied demand below a certain threshold a general stochastic optimization problem is formulated. The distribution of unsatisfied demand is calculated via Monte-Carlo simulations embodied within a grid search algorithm that identifies the feasible region. Thereafter the cost-optimal edge capacity expansion plan is computed by a differential evolution algorithm. Contributions of this article are: 1) consideration of both immediate investment and future risk costs of capacity expansion plans, 2) a generic flow-network model that can be tuned for different real-life applications, 3) addressing the stochastic nature of both supply and demand simultaneously within a systemic risk framework, 4) use of eigenvector centrality for edge grouping in systemic risk analysis. An extensive numerical study is performed to investigate the effects of different edge grouping methods characteristics of stochastic components and cost parameters on the feasible region and optimal solution. The proposed framework is also demonstrated on a case study adapted from ERCOT 13-bus test system. © 2022 Elsevier B.V. All rights reserved.
A Framework for Evaluating Information Transparency in Supply Chains
(IGI Global, 2021-09-28) Erhan Ada; Muhittin Saǧnak; Yigit Kazancoglu; Sunil Luthra; Anil Kumar
Private public profit and non-profit organizations and society as a whole currently face a significant reliable information necessity problem. Especially supply chains need trustworthy information to perform their activities successfully. This study aims to propose a framework and identify how reliability of information can be evaluated and measured through the concept of transparency. In this context dimensions such as comprehensiveness regularity timeliness content scope and user-friendliness are the pillars of the proposed framework. Selected criteria have been used as inputs to develop the information transparency level. The fuzzy analytic network process (ANP) is used to obtain weights of these inputs and data envelopment analysis (DEA) is used for the determination of the efficiency ranking for transparency. Results demonstrated that content scope and comprehensiveness dimensions have 75% impact on the transparency of data. The remaining 25% is affected by timeliness regularity and user-friendliness. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 34
Citation - Scopus: 41
A General BRDF Representation Based on Tensor Decomposition
(WILEY, 2011-10-17) Ahmet Bilgili; Aydin Ozturk; Murat Kurt; Kurt, Murat; Bilgili, Ahmet; Öztürk, Aydin
Generating photo-realistic images through Monte Carlo rendering requires efficient representation of lightsurface interaction and techniques for importance sampling. Various models with good representation abilities have been developed but only a few of them have their importance sampling procedure. In this paper we propose a method which provides a good bidirectional reflectance distribution function (BRDF) representation and efficient importance sampling procedure. Our method is based on representing BRDF as a function of tensor products. Four-dimensional measured BRDF tensor data are factorized using Tucker decomposition. A large data set is used for comparing the proposed BRDF model with a number of well-known BRDF models. It is shown that the underlying model provides good approximation to BRDFs.
Citation - WoS: 6
Citation - Scopus: 8
A goal programming approach to lean production system implementation
(Taylor and Francis Ltd., 2022-03-11) Sadik Serhat Karakütük; Mustafa Arslan Ornek; Ornek, M. Arslan; Karakutuk, S. Serhat
Companies use different production policies to ensure customer demands are satisfied in time. To track the performance of production policies some important Key Performance Indicators related to production control and management are On-Time Delivery (OTD) machine or line productivity (OEE–Overall Equipment Efficiency) optimization of inventory levels between workstations (WIP) customer satisfaction i.e. prioritization of customer orders according to requirements of the customer and backlog minimization. In this study a real-life production management problem is described modelled and solved to improve customer delivery rate and to plan manufacturing orders using lean production tools. Currently the Make-to-Stock policy is used for semi-finished materials. The problems encountered are low customer service level high level of WIP between operations and efficiency losses. Therefore the goal of this study is to increase efficiency (OTD OEE and customer satisfaction) by minimizing setup time decreasing WIP by minimizing earliness backlog quantity level and improving service level by minimizing lateness of orders. Since these goals contradict each other we propose a multi-objective mathematical formulation with a setup carryover strategy. Then we formulate a Goal Programming (GP) model and solve it by using different GP variants and the normalization method. Finally we discuss numerical results and provide our final remarks and conclusions. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 49
Citation - Scopus: 61
A Green Dual-Channel Closed-Loop Supply Chain Network Design Model
(ELSEVIER SCI LTD, 2022-01) Yigit Kazancoglu; Damla Yuksel; Muruvvet Deniz Sezer; Sachin Kumar Mangla; Lianlian Hua; Yuksel, Damla; Sezer, Muruvvet Deniz; Hua, Lianlian; Kazancoglu, Yigit; Mangla, Sachin Kumar
Environmental considerations have become a significant issue in the design of supply chain networks due to today's increasing globalization trends. Therefore supply chain network design needs to be managed in an efficient way to deal with the complex networks involved. The aim of this article is to present a multi-objective optimization model for a green dual-channel supply chain network that handles economic and environmental objectives to optimize network flow. A complex mixed-integer linear programming model (MILP) has been proposed in a green dual-channel and closed-loop supply chain (CLSC) network design. The main objective of the generated MILP model is to investigate the optimal selection of echelons and the optimal selection of transportation alternatives between these echelons in a CLSC network that includes an e-commerce channel structure based on economic and environmental considerations. Environmental aims are achieved by decreasing CO2 emissions and by reducing PM (particulate matter) concentration throughout the network. In addition economic aims are also met by minimizing the overall cost. The validity of the presented model is supported by a case study in the home appliances industry. The results indicate that this model provides valuable knowledge and various alternatives to managers and policymakers depending on the different weight combinations.
Citation - WoS: 53
Citation - Scopus: 62
A green scheduling algorithm for the distributed flowshop problem
(Elsevier Ltd, 2021-09) Yuanzhen Li; Quanke Pan; Kaizhou Gao; M. Fatih Tasgetiren; Biao Zhang; Junqing Li; Tasgetiren, M. Fatih; Li, Jun-Qing; Li, Yuan-Zhen; Pan, Quan-Ke; Gao, Kai-Zhou; Zhang, Biao
In recent years sustainable development and green manufacturing have attracted widespread attention to environmental problems becoming increasingly serious. Meanwhile affected by the intensification of market competition and economic globalization distributed manufacturing systems have become increasingly common. This paper addresses the energy-efficient scheduling of the distributed permutation flowshop (EEDPFSP) with the criteria of minimizing both total flow time and total energy consumption. Considering the distributed and multi-objective optimization complexity an improved NSGAII algorithm (INSGAII) is proposed. First we analyze the problem-specific characteristics and designed new operators based on the knowledge of the problem. Second four constructive heuristic algorithms are proposed to produce high-quality initial solutions. Third inspired by the artificial bee colony algorithm we propose a new colony generation method using the operators designed. Fourth a local intensification is designed for exploiting better non-dominated solutions. The influence of parameter settings is investigated by experiments to determine the optimal parameter configuration of the INSGAII. Finally a large number of computational tests and comparisons have been carried out to verify the effectiveness of the proposed INSGAII in solving EEDPFSP. © 2021 Elsevier B.V. All rights reserved.

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