WoS İndeksli Yayınlar Koleksiyonu

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

Browse

Now showing 1 - 20 of 553

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: 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.
Citation - WoS: 38
Citation - Scopus: 40
A comparative study on conventional and advanced exergetic analyses of geothermal district heating systems based on actual operational data
(Elsevier Science SA, 2013-06) A. Hepbasli; Ali Keçebaş; Hepbasli, Arif; Kecebas, Ali
This paper comparatively evaluates exergy destructions of a geothermal district heating system (GDHS) using both conventional and advanced exergetic analysis methods to identify the potential for improvement and the interactions among the components. As a real case study the Afyon GDHS in Afyonkarahisar Turkey is considered based on actual operational data. For the first time advanced exergetic analysis is applied to the GDHSs in which the exergy destruction rate within each component is split into unavoidable/avoidable and endogenous/exogenous parts. The results indicate that the interconnections among all the components are not very strong. Thus one should focus on how to reduce the internal inefficiency (destruction) rates of the components. The highest priority for improvement in the advanced exergetic analysis is in the re-injection pump (PM-IX) while it is the heat exchanger (HEX-III) in the conventional analysis. In addition there is a substantial influence on the overall system as the total avoidable exergy destruction rate of the heat exchanger (HEX-V) has the highest value. On the overall system basis the value for the conventional exergetic efficiency is determined to be 29.29% while that for the modified exergetic efficiency is calculated to be 34.46% through improving the overall components. © 2013 Elsevier B.V. © 2013 Elsevier B.V. All rights reserved.
A COMPARISON OF DATA MINING TECHNIQUES FOR CREDIT SCORING IN BANKING: A MANAGERIAL PERSPECTIVE
(VILNIUS GEDIMINAS TECH UNIV, 2009-09-30) Huseyin Ince; Bora Aktan
Credit scoring is a very important task for lenders to evaluate the loan applications they receive from consumers as well as for insurance companies which use scoring systems today to evaluate new policyholders and the risks these prospective customers might present to the insurer. Credit scoring systems are used to model the potential risk of loan applications which have the advantage of being able to handle a large volume of credit applications quickly with minimal labour thus reducing operating costs and they may be an effective substitute for the use of judgment among inexperienced loan officers thus helping to control bad debt losses. This study explores the performance of credit scoring models using traditional and artificial intelligence approaches: discriminant analysis logistic regression neural networks and classification and regression trees. Experimental studies using real world data sets have demonstrated that the classification and regression trees and neural networks outperform the traditional credit scoring models in terms of predictive accuracy and type II errors.
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.
A constraint programming approach to a real-world workforce scheduling problem for multi-manned assembly lines with sequence-dependent setup times
(TAYLOR & FRANCIS LTD, 2023-07-13) Funda Guner; Abdul K. Gorur; Benhur Satir; Levent Kandiller; John H. Drake
For over five decades researchers have presented various assembly line problems. Recently assembly lines with multiple workers at each workstation have become very common in the literature. These lines are often found in the manufacturing of large vehicles where workers at a workstation may perform their assigned tasks at the same time. Most research on multi-manned assembly lines focuses on balancing tasks and workers among workstations and scheduling tasks for workers. This study however concentrates on assigning tasks to workers already assigned to a specific workstation rather than balancing the entire line. The problem was identified through an industrial case study at a large vehicle manufacturing company. The study presents two methods one using mixed integer linear programming and the other using constraint programming to minimise the number of workers required on a multi-manned assembly line with sequence-dependent setup times. The results of the computational experiments indicate that the constraint programming method performs better than the mixed integer linear programming method on several modified benchmark instances from the literature. The constraint programming model is also tested on the real-world scenario of our industrial case study and leads to significant improvements in the productivity of the workstations.
Citation - WoS: 55
Citation - Scopus: 60
A constructive aisle design model for unit-load warehouses with multiple pickup and deposit points
(Elsevier, 2014-07) Kevin R. Gue; Russell D. Meller; Meller, R. D.; Ozturkoglu, O.; Gue, K. R.
We develop a network-based warehouse model of individual pallet locations and their interactions with appropriate cross aisles in order to evaluate the expected travel distance of a given design. The model is constructive in that it uses Particle Swarm Optimization to determine the best angles of cross aisles and picking aisles for multiple pre-determined pickup and deposit (P&D) points in a unit-load warehouse. Our results suggest that alternative designs offer reduced expected travel distance but at the expense of increased storage space. The opportunity for benefit also seems to decline as P&D points increase in number and dispersion. © 2013 Elsevier B.V. All rights reserved. © 2014 Elsevier B.V. All rights reserved.
A Content Analysis of the AKP's Honorable Foreign Policy Discourse: The Nexus of Domestic-International Politics
(ROUTLEDGE JOURNALS TAYLOR & FRANCIS LTD, 2014-01-02) Ugur Cevdet Panayirci; Emre Iseri
Abstract This article examines political leaders' framing strategies during times of public diplomacy crisis. By focusing on the nexus of domestic-international politics it argues that during public diplomacy crises policy-makers would like to utilize their speech acts on foreign policy issues to manage expectations of domestic public opinion. This paper's main contention is to demonstrate that the head of AKP (Adalet ve Kalkinma Partisi) government Recep Tayyip Erdogan has instrumentalized his foreign policy speeches with the label of honorable to legitimize AKP's practices at the domestic level.
A decision framework for incorporating the coordination and behavioural issues in sustainable supply chains in digital economy
(SPRINGER, 2022-07-04) Patanjal Kumar; Sachin Kumar Mangla; Yigit Kazancoglu; Ali Emrouznejad
Global warming climate change and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution greenhouse effect poor working conditions child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system actor objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance reciprocity fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance social performance and channel efficiency of the supply chain thereby ensuring sustainability and socio welfare of all the supply chain.
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 disassembly line balancing problem with fixed number of workstations
(ELSEVIER, 2016-03) Eda Goksoy Kalaycilar; Meral Azizoglu; Sencer Yeralan
In this study a Disassembly Line Balancing Problem with a fixed number of workstations is considered. The product to be disassembled comprises various components which are referred to as its parts. There is a specified finite supply of the product to be disassembled and specified minimum release quantities (possible zero) for each part of the product. All units of the product are identical however different parts can be released from different units of the product. There is a finite number of identical workstations that perform the necessary disassembly operations referred to as tasks. We present several upper and lower bounding procedures that assign the tasks to the workstations so as to maximize the total net revenue. The computational study has revealed that the procedures produce satisfactory results. (C) 2015 Elsevier B.V. and Association of European Operational Research Societies (EURO) within the International Federation of Operational Research Societies (IFORS). All rights reserved.
A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities
(ELSEVIER SCIENCE INC, 2014-02) Jun-Qing Li; Quan-Ke Pan; M. Fatih Tasgetiren
This paper presents a novel discrete artificial bee colony (DABC) algorithm for solving the multi-objective flexible job shop scheduling problem with maintenance activities. Performance criteria considered are the maximum completion time so called makespan the total workload of machines and the workload of the critical machine. Unlike the original ABC algorithm the proposed DABC algorithm presents a unique solution representation where a food source is represented by two discrete vectors and tabu search (TS) is applied to each food source to generate neighboring food sources for the employed bees onlooker bees and scout bees. An efficient initialization scheme is introduced to construct the initial population with a certain level of quality and diversity. A self-adaptive strategy is adopted to enable the DABC algorithm with learning ability for producing neighboring solutions in different promising regions whereas an external Pareto archive set is designed to record the non-dominated solutions found so far. Furthermore a novel decoding method is also presented to tackle maintenance activities in schedules generated. The proposed DABC algorithm is tested on a set of the well-known benchmark instances from the existing literature. Through a detailed analysis of experimental results the highly effective and efficient performance of the proposed DABC algorithm is shown against the best performing algorithms from the literature. (C) 2013 Elsevier Inc. All rights reserved.
A discrete artificial bee colony algorithm for the total flowtime minimization in permutation flow shops
(ELSEVIER SCIENCE INC, 2011-08) M. Fatih Tasgetiren; Quan-Ke Pan; P. N. Suganthan; Angela H-L Chen
Obtaining an optimal solution for a permutation flowshop scheduling problem with the total flowtime criterion in a reasonable computational timeframe using traditional approaches and optimization tools has been a challenge. This paper presents a discrete artificial bee colony algorithm hybridized with a variant of iterated greedy algorithms to find the permutation that gives the smallest total flowtime. Iterated greedy algorithms are comprised of local search procedures based on insertion and swap neighborhood structures. In the same context we also consider a discrete differential evolution algorithm from our previous work. The performance of the proposed algorithms is tested on the well-known benchmark suite of Taillard. The highly effective performance of the discrete artificial bee colony and hybrid differential evolution algorithms is compared against the best performing algorithms from the existing literature in terms of both solution quality and CPU times. Ultimately 44 out of the 90 best known solutions provided very recently by the best performing estimation of distribution and genetic local search algorithms are further improved by the proposed algorithms with short-term searches. The solutions known to be the best to date are reported for the benchmark suite of Taillard with long-term searches as well. (C) 2011 Elsevier Inc. All rights reserved.
Citation - WoS: 38
Citation - Scopus: 55
A discrete cross aisle design model for order-picking warehouses
(ELSEVIER SCIENCE BV, 2019-06) Deniz Hoser; Omer Ozturkoglu; Hoser, Deniz; Ozturkoglu, Omer
In this paper we develop new warehouse designs that provide a reduction in travel distance for the order-picking operation which is the most costly operation and the one most closely associated with order delivery time. For this purpose we propose a new layout problem called discrete cross aisle warehouse design. In this problem a linear middle cross aisle is divided into segments called tunnels on each picking aisle. In order to calculate average tour length for the proposed design problem we develop an efficient algorithm that solves the order-picking problem optimally. A harmony search algorithm is used to find optimal tunnel positions that minimize the average tour length under a randomized storage policy by searching the space of all possible designs. A numerical study shows that for small size order lists the best-found solutions have similar layouts to the traditional two-block designs. As the number of locations to be visited increases tunnel positions move away from the center of the warehouse and construct a segregated tunnels on the layout. Compared to the traditional two-block layouts new tunnel based designs provide savings of up to 7% average savings in order-picking tour length. (C) 2018 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.
Citation - WoS: 48
Citation - Scopus: 69
A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions
(Elsevier Inc., 2021-09) Yigit Kazancoglu; Muhittin Saǧnak; Sachin Kumar Kumar Mangla; Muruvvet Deniz Sezer; Melisa Ozbiltekin-Pala; Sezer, Muruvvet Deniz; Pala, Melisa Ozbiltekin; Kazancoglu, Yigit; Sagnak, Muhittin; Mangla, Sachin Kumar
This study determines the potential barriers to achieving circularity in dairy supply chains, it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘economic’ ‘environmental’ ‘social and legal’ ‘technological’ ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning optimization data mining cloud computing artificial neural network statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers ‘economic’ was of the highest importance followed by ‘technological’ ‘environmental’ ‘strategic’ ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’ ‘machine learning’ ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains. © 2021 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.
Citation - WoS: 11
Citation - Scopus: 16
A hybrid Bayesian approach for assessment of industry 4.0 technologies towards achieving decarbonization in manufacturing industry
(Elsevier Ltd, 2024-04) Devesh Kumar; Gunjan Soni; Fauzia Jabeen; Neeraj Kumar Tiwari; Gorkem Sariyer; Bharti Ramtiyal; Ramtiyal, Bharti; Jabeen, Fauzia; Soni, Gunjan; Kumar Tiwari, Neeraj; Sariyer, Gorkem; Kumar, Devesh; Tiwari, Neeraj Kumar
Since the 1st Industrial Revolution the Earth's atmosphere has warmed due to human activities like deforestation burning fossil fuels for energy generation and livestock raising. Without preventative measures the Earth's atmosphere would warm by 2 °C before the next Industrial Revolution. Thus it has become crucial to move toward a low-carbon economy. Reaching carbon neutrality means cutting our carbon footprint to zero. Innovative research methods and technologies can play a significant role in supporting the economy in its carbon reduction efforts. Industry 4.0 (I4.0) technologies hold great potential for decarbonizing the economy. However there is a need to explore and utilize this potential effectively. This study aims to address this by developing a methodology that identifies relevant attributes and critical measures from existing literature mapping them with I4.0 technologies. Using a MCDM approach each measure is prioritized based on importance. To better understand the interrelationships between these attributes and I4.0 technologies the Bayesian Network (BN) method is employed. This approach enables the exploration of dependencies and influences among variables. By implementing this four-stage strategy economies can make informed decisions and prioritize actions contributing to carbon neutrality while leveraging the benefits of I4.0 technologies. This approach offers a comprehensive framework for guiding economies on their path towards carbon neutrality considering the potential of I4.0 technologies and the importance of various attributes identified through literature. © 2024 Elsevier B.V. All rights reserved.

Browse

Browsing WoS İndeksli Yayınlar Koleksiyonu by WoS Q "Q1"