Article
Computer Science, Artificial Intelligence
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri
Summary: The integration of Circular Economy (CE) principles in Supply Chain (SC) is crucial for sustainable competitive advantage, but faces challenges of uncertainty and long-term decision-making in Closed-Loop Supply Chain Network Design (CLSCND). This study proposes a scenario-based possibilistic-stochastic programming approach to simultaneously consider cognitive and random uncertainties while achieving CE goals.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Green & Sustainable Science & Technology
M. Boronoos, M. Mousazadeh, S. Ali Torabi
Summary: This study introduces a novel multi-objective mixed integer nonlinear programming model for closed-loop green supply chain network design problem, aiming to minimize total costs, total CO2 emissions, and robustness costs simultaneously. By utilizing a robust flexible-possibilistic programming approach to handle flexible constraints and uncertainty in parameters, the study suggests that the carbon cap-and-trade policy is superior in most cases.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2021)
Article
Engineering, Chemical
Congqin Ge, Lifeng Zhang, Wenhui Yang, Zhihong Yuan
Summary: Traditional supply chains are becoming more volatile, leading to an increasing adoption of mobile modularization. This allows for flexible capacity adjustments and facility relocations to tackle market volatility. A mixed-integer linear programming model is proposed for closed-loop supply chain network planning with modular distribution and collection facilities. The model is further extended to incorporate uncertain customer demands and recovery rates, and is efficiently solved using a tailored stochastic dynamic dual integer programming approach. Computational experiments demonstrate the effectiveness of the proposed algorithm and the benefits of mobile modules in high temporal and spatial variability of customer demand.
Article
Operations Research & Management Science
Mohsen Momenitabar, Zhila Dehdari Ebrahimi, Mohammad Arani, Jeremy Mattson
Summary: Reconfiguring the structure of the supply chain network is a crucial decision in designing a supply chain network. This study proposes a Closed-Loop Blood Supply Chain Network (CLBSCN) model that considers blood group compatibility, ABO-Rh(D), and blood product shelf life. By utilizing a fuzzy multi-objective MINLP model, the study aims to optimize the network's costs and service levels. The model is tested and validated through a real case study and sensitivity analysis.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Environmental Sciences
Fariba Goodarzian, Peiman Ghasemi, Ernesto DR. Santibanez Gonzalez, Erfan Babaee Tirkolaee
Summary: Configuration of sustainable supply chains for agricultural products is a growing research field that lacks models integrating social impacts and environmental effects for citrus supply chain configuration. This study proposes a novel multi-objective Mixed-Integer Linear Programming model to design the sustainable citrus Closed-Loop Supply Chain network. The efficiency of suggested algorithms is tested using assessment metrics and convergence analysis, showing that the SPEA-II algorithm has superior efficiency over PESA-II.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2023)
Article
Green & Sustainable Science & Technology
Hossein Savoji, Seyed Meysam Mousavi, Jurgita Antucheviciene, Miroslavas Pavlovskis
Summary: This paper presents a new mathematical model aiming to minimize CO2 emission and total costs in the biofuel supply chain, creating a green supply chain network. Uncertain data regarding CO2 emission and biofuel demand were addressed using a robust possibilistic programming approach. The applicability and performance of the model were demonstrated based on an experimental example.
Article
Environmental Sciences
Leyla Ozgur Polat, Askiner Gungor
Summary: This study proposes a mixed integer programming model for decision-makers to manage their activities on the WEEE closed-loop supply chain network, integrating product returns with different quality and damage levels. The results indicate that the capacity balance among stores, producers, and recovery centers is vital to make the network profitable and sustainable.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Hadi Moheb-Alizadeh, Robert Handfield, Donald Warsing
Summary: This paper discusses how to balance sustainability and efficiency in supply chain network design, by introducing methods such as multi-objective programming, data envelopment analysis, and Lagrangian relaxation algorithm. The application of the methods is demonstrated through a case study, highlighting the integration of efficiency results in improving economic aspects of sustainability and social responsibility outcomes, as well as the trade-offs between efficiency and environmental impacts.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Multidisciplinary
M. S. Al-Ashhab
Summary: This research aimed to develop a multi-objective MILP mathematical model for the design and planning of closed-loop supply chain networks (CLSCN) in order to tackle the challenges posed by global crises such as COVID-19 pandemic and the Russian-Ukrainian war. The model considered the uncertainty in both the supplying capacity of raw materials and the return rate of used products, with the goal of maximizing total profit, minimizing total cost, and maximizing overall customer service level (OCSL) using the e-lexicographic procedure.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Muhammad Ridwan Andi Purnomo, Ivan Darma Wangsa, Novrianty Rizky, Wakhid Ahmad Jauhari, Ismi Zahria
Summary: This study develops a mathematical model to investigate a sustainable and traceable fish closed-loop supply chain network problem, considering the carbon emissions of transport, production, and warehouse activities. A numerical example is used to verify the proposed model and provide managerial insight to the relevant industry.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Kafiye Salcuk, Cenk Sahin
Summary: Designing and modeling a supply chain network is crucial for determining costs and time in bringing goods to market. Closed-loop supply chains contribute to sustainability goals and an optimized network can reduce carbon footprint, improve delivery quality, and enhance customer experience and differentiation.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Lily Poursoltan, Seyed-Mohammad Seyed-Hosseini, Armin Jabbarzadeh
Summary: This study introduces a green closed-loop supply chain framework for ventilators, addressing environmental sustainability and carbon emissions constraints, using a stochastic optimization model with strategic and tactical decision making. The proposed model is applied to a case study of Iranian medical ventilator production to analyze the impact of carbon emissions and demand variations on the optimal solution in the COVID-19 pandemic context. Sensitivity analyses show the managerial dimensions of the proposed model under the COVID-19 pandemic.
Article
Management
Milad Mohammadi, Alibakhsh Nikzad
Summary: This paper aims to design a mathematical model for sustainable closed-loop supply chains during the COVID-19 outbreak. The proposed model considers multiple objectives, including minimizing total cost, carbon emission, and infection risk, and maximizing social benefits. Stochastic demands, supplier selection, and facility disruptions are taken into account. The stochastic model is transformed into a deterministic model using the CCP approach. The effects of COVID-19 on network performance are examined using 30 test datasets. The results show that the model with COVID-19 has a higher total inventory and aggregated objectives, indicating a greater distance from optimal objectives. However, the model without COVID-19 has higher computational efficiency. Sensitivity analyses are conducted, and policy implications are proposed, such as adjusting management focus based on demand forecasts and allocating resources effectively.
OPERATIONS MANAGEMENT RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Ali Pedram, Shahryar Sorooshian, Freselam Mulubrhan, Afshin Abbaspour
Summary: In recent years, there has been a growing concern for environmental protection and sustainability. Designing an efficient supply chain network that meets the expectations of businesses and customers while focusing on environmental protection has become a trend in the commercial world. This study presents a theoretical model that incorporates vehicle routing problems into the closed-loop supply chain network, aiming to improve efficiency in both environmental protection and profitability. The model is developed using mixed-integer-linear-programming and fuzzy-stochastic mathematical programming methods. Numerical examples demonstrate the validity of the proposed model, suggesting its potential to enhance profitability in daily operations.
Article
Management
Prem Chhetri, Mahsa Javan Nikkhah, Hamed Soleimani, Shahrooz Shahparvari, Ashkan Shamlou
Summary: This paper designs an optimal closed-loop supply chain network to examine the possibility of remanufacturing end-of-life ships. By using a mixed-integer linear programming model, the optimal number and location of remanufacturing for building EoL ships are determined, and the required capital and variable costs for establishing and operating remanufacturing centers are calculated. If remanufacturing 30 ships a year, the discounted payback period of this project is estimated to be less than two years.
INTERNATIONAL JOURNAL OF LOGISTICS MANAGEMENT
(2022)
Article
Business
Adil Baykasoglu, Kemal Subulan, Hulya Gucdemir, Nurhan Dudakli, Derya Eren Akyol
ENGINEERING ECONOMIST
(2020)
Article
Computer Science, Interdisciplinary Applications
Adil Baykasoglu, Cengiz Baykasoglu
ENGINEERING WITH COMPUTERS
(2020)
Article
Computer Science, Cybernetics
Adil Baykasoglu, Ilker Golcuk
Article
Operations Research & Management Science
Adil Baykasoglu, Burcu Kubur Ozbel
Summary: The paper introduces a new approach based on the framework of interval analysis to solve maximum flow problems in uncertain networks. By employing risk explicit interval linear programming model and collaborative game theoretic approach in multiple-owners network, the proposed method aims to maintain stable network flow under interval uncertainty.
OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Adil Baykasoglu, Nurhan Dudakli, Mumin Emre Senol, Feyzi Komurcu
Summary: This paper aims to optimize the efficiency of spar cap production in wind turbine blade production by introducing a new optimization problem and developing two mathematical programming models. Solving the roll allocation problem optimally can significantly reduce workers' walking time/distance, improve manufacturing practices, indirectly reduce total operation time, and increase productivity in wind turbine blade production.
ENGINEERING WITH COMPUTERS
(2021)
Article
Engineering, Industrial
Adil Baykasoglu
Summary: This study optimised cutting conditions in multi-pass milling using a weighted superposition attraction algorithm, satisfying all cutting constraints and providing the best solutions for all test cases within a reasonable computational time.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Operations Research & Management Science
Adil Baykasoglu, Nurhan Dudakli, Kemal Subulan, A. Serdar Tasan
Summary: This paper explores the importance of fleet planning in intermodal transportation and proposes a holistic approach to address the complexity of fleet planning in comparison with unimodal systems. Through a comprehensive mixed-integer linear programming model, the optimization of fleet planning is achieved.
OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Fehmi Burcin Ozsoydan, Adil Baykasoglu
Summary: The Flower Pollination Algorithm (FPA) simulates the pollination behavior of flowers to solve global optimization problems, and has been extended and modified to improve performance. Modifications include adjustments to the pollination mechanism and convergence control, as well as the extension to a species-based algorithm for independent search of promising regions. These modifications show significant improvements in solving various optimization problems.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Adil Baykasoglu, Fatma S. Madenoglu
Summary: This study proposed a GRASP algorithm for simultaneous dynamic scheduling of operations and preventive maintenance activities in flexible job shops, considering various dynamic events and maintenance strategies. The results demonstrated that this approach is effective in improving performance in dynamic flexible job shop scheduling environments.
Article
Computer Science, Artificial Intelligence
Adil Baykasoglu, Elif Ercan
Summary: The paper examines the rank reversal problem in MADM methods, focusing on the WASPAS method. Computational experiments show that traditional normalization techniques lead to rank reversal problems in WASPAS, but using modified normalization techniques can mitigate this issue.
Article
Computer Science, Cybernetics
Adil Baykasoglu, Burcu Felekoglu, Ceylin Unal
Summary: The usage of learning management systems (LMSs) has become widespread due to the disruption caused by the COVID-19 pandemic. Selecting a suitable LMS is a complex decision-making problem that involves considering multiple criteria and inputs from different parties. Usability evaluation of LMS is a critical step in the decision-making process. This study proposes an axiomatic design procedure (ADP) based approach for the perceived usability evaluation of SAKAI-LMS. The ADP method allows easy data fusion and setting performance targets. A questionnaire is developed to collect data on usability criteria and their importance from system users. The proposed approach provides an easy and practical evaluation of perceived usability of LMSs for decision makers. It has been verified through a real-life case study at an academic department.
Article
Computer Science, Artificial Intelligence
Kemal Subulan, Bilge Varol, Adil Baykasoglu
Summary: This paper introduces a new unequal-area capability-based facility layout design problem and proposes a MINLP model and a heuristic decomposition-based iterative solution approach to solve it. Computational results demonstrate the effectiveness and applicability of the proposed approach through illustrative examples and a real-life application.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Manufacturing
Cengiz Baykasoglu, Adil Baykasoglu, Erhan Cetin
Summary: The objective of this study is to find the optimum design configurations for functionally graded lattice structure filled aluminum tubes under multiple impact loading conditions. The optimal design is sought for maximizing specific energy absorption and minimizing peak crush force by considering base strut diameter, draft angle, and aspect ratio as filler material design parameters. Finite element simulations, regression meta-models, and an attraction-repulsion algorithm were employed to establish the design space, estimate objective function values, create design alternatives, and seek their optimum combinations. The results showed that the crashworthiness performance of hybrid structures can be effectively enhanced by selecting appropriate lattice filler parameters, with a potential improvement of up to 76% in specific energy absorption for square tubes. This study provides a guideline for the optimum design of functionally graded lattice structure filled thin-walled structures under multiple impact loading conditions.
INTERNATIONAL JOURNAL OF CRASHWORTHINESS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Adil Baykasoglu, Mumin Emre Senol
Summary: This study demonstrates the improvement of metaheuristic algorithms performance through the application of Levy flight to the WSAR algorithm. The experimental results show that the Levy flight WSAR algorithm performs better than other algorithms in constrained design optimization problems.
PROCEEDINGS OF 7TH INTERNATIONAL CONFERENCE ON HARMONY SEARCH, SOFT COMPUTING AND APPLICATIONS (ICHSA 2022)
(2022)
Article
Sociology
Nurhan Dudakli, Burcu Felekoglu, Adil Baykasoglu
Summary: This paper explores the reverse innovation process of multinational enterprises in emerging markets and identifies the key factors for successful reverse innovation, including the quality of innovation ideas, collaboration between MNEs and local enterprises, and unique diffusion strategies.
INNOVATION-THE EUROPEAN JOURNAL OF SOCIAL SCIENCE RESEARCH
(2022)
Article
Engineering, Industrial
Xiaoliang Yan, Reed Williams, Elena Arvanitis, Shreyes Melkote
Summary: This paper extends prior work by developing a semantic segmentation approach for machinable volume decomposition using pre-trained generative process capability models, providing manufacturability feedback and labels of candidate machining operations for query 3D parts.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
