Article
Environmental Sciences
Yu Gan, Amgad Elgowainy, Zifeng Lu, Jarod C. Kelly, Michael Wang, Richard D. Boardman, Jason Marcinkoski
Summary: Solar photovoltaic (PV) electricity is an important source of electricity generation in the pursuit of net-zero carbon emissions. However, the growth of solar electricity leads to increased material demands and greenhouse gas (GHG) emissions from silicon and PV manufacturing. Analyzing the supply chain for the U.S. market, it is found that the majority of GHG emissions come from PV panel production processes in China and other Asia-Pacific countries. Moving manufacturing to the U.S. would reduce GHG emissions and, coupled with a decarbonized grid and improved PV conversion efficiency, the embodied GHG emissions of solar electricity in the U.S. could be significantly reduced.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Ana Paula Barbosa-Povoa, Jose M. Pint
Summary: This paper presents a framework for supply chain resilience and discusses the main challenges and opportunities in academia and industry. It focuses on industrial gas supply chains impacted by COVID-19, geopolitical instability, and the increasing availability of renewable energy sources for the hydrogen value chain.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Environmental Sciences
Sourena Rahmani, Alireza Goli
Summary: The excessive consumption of fossil fuels has led to environmental damage, prompting the global community to search for a suitable alternative. Biodiesel, a clean and eco-friendly fuel, has emerged as one viable option. To promote mass-level production of biodiesel, a sustainable supply chain network is necessary. This study proposes a mathematical model and scenario-based robust optimization approach to design such a network, resulting in achievable and efficient production and distribution of biodiesel fuel.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Ayberk Soyer, Erhan Bozdag, Cigdem Kadaifci, Umut Asan, Seyda Serdarasan
Summary: Supply chains are vulnerable to disruptive events, posing risks to all parties involved. This study proposes a new approach to examine the structure of sustainable supply chain risks and their impact on performance. The findings reveal that risks linked to economic, social, and environmental sustainability have a negative impact on supply chain performance.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Yaqin Yuan, Wei Li
Summary: This study investigates the impact of supply chain risk (SCR) information processing capabilities and supply chain finance (SCF) on supply chain resilience, with the moderating effect of environmental uncertainty on the relationship between SCF and supply chain resilience. The findings show that SCR information processing capabilities significantly affect both SCF and supply chain resilience. SCF plays a partial mediating role in the relationship between SCR information processing capabilities and supply chain resilience. Moreover, environmental uncertainty moderates the relationship between SCF and supply chain resilience.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2022)
Article
Engineering, Industrial
Keivan Tafakkori, Fariborz Jolai, Reza Tavakkoli-Moghaddam
Summary: This paper presents decentralized capacity planning models for different types of supply chain entities, aiming to enhance their resilience. Novel resilience metrics are developed to measure the proximity of capacities to disruptions, and optimization models are used to select business continuity plans that maximize resilience and cost-efficiency. Uncertainties associated with recovery time and disruptions are addressed using a robust-stochastic optimization method, and disruption scenarios are simulated using a discrete-time Markov chain. Computational tests confirm the robustness, validity, and generality of the proposed models.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Artificial Intelligence
Honghua Shi, Yaodong Ni
Summary: This paper focuses on the problems faced by supply chain resilience design and proposes two uncertain programming models to address the risks in the supply chain. By controlling costs and handling uncertainty, these models can help make better decisions. The proposed models are validated through examples and a practical case, demonstrating their effectiveness and feasibility.
Article
Computer Science, Information Systems
Jiabao Lin, Shunzhi Lin, Jose Benitez, Xin (Robert) Luo, Aseel Ajamieh
Summary: Drawing on resource orchestration theory, this study argues that deploying digitally-driven business capability aligned with supply chain governance can improve supply chain resilience. The empirical analysis conducted on a sample of Chinese agriculture firms confirmed three fit mechanisms (complementing fit, balancing fit, and configuring fit) between digitally-driven business capability and supply chain governance, and their impacts on supply chain resilience. This research provides novel insights into the specific mechanisms through which digitally-driven business capability and supply chain governance jointly enhance supply chain resilience. Implications for management and future Information Systems (IS) research are discussed.
INFORMATION & MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Huili Pei, Hongliang Li, Yankui Liu
Summary: This paper addresses the issue of demand uncertainty in dual-channel supply chain, proposing a novel uncertainty distribution set to model ambiguous demand distribution and developing a distributionally robust bilevel optimization framework for capital-constrained scenarios. Different financing strategies and their impact on manufacturers are investigated, revealing that demand ambiguity and equity ratio can influence the manufacturer's equilibrium financing strategy.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Qin Zhang, Caijie Liu, Shaoxiang Zheng
Summary: The management of end-of-life solar photovoltaic waste is a significant concern due to its environmental and economic impact. This study focuses on the recycling process from a supply chain perspective and analyzes the effects of investment decisions and pricing strategies. The findings show that subsidies are more effective than penalties for low-cost investments, while both policies have positive effects on the formal treatment rate of high-cost investments.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Review
Business
Marta Negri, Enrico Cagno, Claudia Colicchia, Joseph Sarkis
Summary: This study finds that the concept of sustainable supply chains is more established with general agreement on its theoretical foundations. On the other hand, supply chain resilience is relatively less mature. The relationships between the two topics are often incoherent, with confusion on establishment practices and lack of clarity on practices that could advance both areas simultaneously.
BUSINESS STRATEGY AND THE ENVIRONMENT
(2021)
Article
Green & Sustainable Science & Technology
Hotlan Siagian, Zeplin Jiwa Husada Tarigan, Ferry Jie
Summary: The study investigates the impact of supply chain integration on business performance in Indonesian manufacturing companies, finding that supply chain integration significantly affects innovation system, supply chain flexibility, and supply chain resilience. Innovation systems and supply chain flexibility enhance supply chain resilience by dealing with sudden changes.
Article
Computer Science, Interdisciplinary Applications
Ghulam Hussain, Mian Sajid Nazir, Muhammad Amir Rashid, Maheen Abdul Sattar
Summary: This study explores the direct and indirect effects of supply chain resilience enablers on supply chain disruption orientation, as well as the moderating role of supply chain complexity. The findings suggest that supply chain resilience significantly mediates the relationship between resilience enablers and disruption orientation, with supply chain complexity positively moderating this relationship. The study contributes to the understanding of how firms can build resilient supply chain systems to recover from disruptions and strengthen response management systems.
JOURNAL OF ENTERPRISE INFORMATION MANAGEMENT
(2023)
Article
Computer Science, Interdisciplinary Applications
Cecil Ash, Claver Diallo, Uday Venkatadri, Peter VanBerkel
Summary: This paper presents a multi-period multi-objective distributionally robust optimization framework for enhancing the resilience of personal protective equipment (PPE) supply chains against disruptions caused by pandemics. The study investigates the effects of model conservatism on procurement decisions and recommends the use of distributionally robust optimization during pandemics.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Songtao Zhang, Yi Cui
Summary: This article investigates how to effectively manage dynamic working capital in uncertain supply chain systems, by introducing fuzzy control theory and designing a robust financing strategy to suppress the impact of uncertainties and reduce financing costs.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Operations Research & Management Science
Zahra Homayouni, Mir Saman Pishvaee, Hamed Jahani, Dmitry Ivanov
Summary: This article investigates sustainability strategies for carbon regulation mechanisms and proposes a multi-objective programming model to support decision-making in supply chains. The study finds that governmental incentives for carbon cap-and-trade policies can effectively reduce pollution in supply chains.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Mehdi Alizadeh, Mir Saman Pishvaee, Hamed Jahani, Mohammad Mahdi Paydar, Ahmad Makui
Summary: In this study, a viable healthcare network design for a pandemic is developed using a multi-stage stochastic approach. The proposed multi-level network includes health centers, computed tomography scan centers, hospitals, and clinics, and aims to maximize patient recovery probability, minimize network costs, and reduce the Coronavirus death rate. An investigation of a real case study in Iran demonstrates the model's applicability and provides a comparison between healthcare supply chain network design in a pandemic and a normal situation.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Seyyed Jalaladdin Hosseini Dehshiri, Maghsoud Amiri, Laya Olfat, Mir Saman Pishvaee
Summary: The Closed-Loop Supply Chain Network Design (CLSCND) addresses the economic and environmental issues of returned products, which is a significant decision problem accompanied by uncertainty. This study proposes a novel flexible, probabilistic, and stochastic programming approach based on robust optimization with a focus on the Me measure. Simulation and evaluation of the results demonstrate that the suggested model performs well.
APPLIED SOFT COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Zahra Alidoosti, Ahmad Sadegheih, Kannan Govindan, Mir Saman Pishvaee
Summary: In a circular economy, municipal solid waste will be used as a resource, requiring the design of a product-oriented waste management network. The production of diverse bioenergies is crucial, making it necessary to study the waste management network. A sustainable waste management network was designed to extract various bioenergies, considering economic, environmental, and social sustainability under uncertain conditions. The proposed model used a multi-objective possibilistic mixed-integer non-linear programming approach and interactive fuzzy programming methods to handle uncertainty.
JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY
(2023)
Article
Computer Science, Artificial Intelligence
Sajjad Rahmanzadeh, Mir Saman Pishvaee, Mohammad Reza Rasouli
Summary: This paper explores the impact of the open innovation concept on product design and supply chain master planning. The study considers complex uncertainties in co-design processes, financial challenges, and integration of innovative designs with supply chain planning. A robust fuzzy-stochastic optimization model is proposed to integrate product design and supply chain activities, accounting for different types of uncertainties. The model's contributions include integrating financial and physical flows, using a novel pricing mechanism, and considering external innovations. Results show the superiority of the model in supporting managerial decisions in mid-term planning.
Article
Engineering, Civil
Ali Katebi, Mir Saman Pishvaee, Ali Mohebalizadeh, Ashkan Pazhuhandeh, Bahareh Katebi
Summary: This study proposes a robust optimization approach to modify the programming model of earthwork allocations in road construction. The model considers uncertainties in borrow pit and disposal site capacities and earthwork costs, aiming to minimize project costs while mitigating problem-based constraints. The results show that the robust model ensures feasible solutions with minimized constraint violations and deviations from optimality when there are changes in the input within a given range.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING
(2023)
Article
Energy & Fuels
Abolfazl Rasekh, Farhad Hamidzadeh, Hadi Sahebi, Mir Saman Pishvaee
Summary: Nowadays, the world is facing a major challenge due to population growth, rising global energy demand, increasing water consumption, carbon emissions, and excessive use of fossil fuels. Biomass is considered as one of the most attractive energy sources with positive effects on the economy, environment, and society. Therefore, the design of biomass supply chain networks has gained more attention. Additionally, studying the water-energy-carbon (WEC) nexus is essential for society's sustainable development.
ENERGY SCIENCE & ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Amir Arabsheybani, Alireza Arshadi Khamseh, Mir Saman Pishvaee
Summary: Traditional supply chain designers have not taken environmental factors into account during the design process. However, environmental protection is an important criteria that needs to be evaluated according to global regulations. Perishable items in the food supply chain have limited shelf life and contribute to significant waste, affecting both profit and environmental criteria. Two main solutions to decrease waste are improving packaging and optimizing planning. This study proposes a mathematical model that incorporates efficient biodegradable nano-silver packaging and multi-objective optimization to maximize profit and minimize carbon emissions. The results show that reducing carbon emissions is possible without increasing costs, and using nano-silver packaging positively impacts profit and environmental sustainability.
ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY
(2023)
Article
Energy & Fuels
Shayan Mohseni, Mir Saman Pishvaee, Reza Dashti
Summary: This paper proposes a data-driven two-level transactive energy management framework to address the main issues of trading mechanism design, uncertainty treatment, and privacy protection in networked microgrids. The framework involves determining optimal strategies for internal scheduling and external trading, as well as fair allocation of trading benefits. The uncertainties of renewable energy sources are captured using a robust optimization approach with a robust kernel density estimation (RKDE) technique. The proposed model is solved in a distributed manner using the alternating direction method of multipliers (ADMM) and the augmented Lagrange-based alternating direction inexact Newton (ALADIN) algorithms.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Computer Science, Artificial Intelligence
Amin Reza Kalantari Khalil Abad, Farnaz Barzinpour, Mir Saman Pishvaee
Summary: This study establishes a decision-making framework for industrial activities during global shocks and transformations, such as the COVID-19 pandemic, and introduces a new type of uncertainty called deep dynamic uncertainty. By using a Mixed-Integer Linear Programming model and an Augmented Adjustable Column-Wise Robust Optimization algorithm, the study effectively deals with demand uncertainty during the COVID-19 outbreak.
APPLIED SOFT COMPUTING
(2023)
Review
Computer Science, Interdisciplinary Applications
Tahereh Haghpanah, Mohammad Amin Sobati, Mir Saman Pishvaee
Summary: Microalgae have potential as feedstock for biofuels and other value-added products, but the variety in processing pathways is a challenge for commercialization. The superstructure optimization method is a promising solution, and this study reviews past research and identifies future research directions in microalgae-based bio-refinery process synthesis, focusing on the superstructure optimization approach. The study categorizes relevant papers based on feedstocks, end products, mathematical models, objective functions, sustainability, solution methods, and economic and environmental analysis, and describes existing research gaps.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Amin Reza Kalantari Khalil Abad, Farnaz Barzinpour, Mir Saman Pishvaee
Summary: This study proposes a novel biobjective model for the design of a green closed-loop pomegranate supply chain based on the value chain to ensure food security and maximize the benefits of circular economy. A thermochemical conversion process and a hybrid risk-neutral and risk-averse multi-stage stochastic programming approach are developed to address supply uncertainty. The proposed approach is validated using the expected value of perfect information and value of stochastic solution metrics. A real case study in Iran demonstrates the applicability of the model, showing savings of up to 1% and 1.76% in worst-case cost compared to the deterministic model based on the value of stochastic solution metric.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Engineering, Industrial
Omid Abdolazimi, Mir Saman Pishvaee, Mohammad Shafiee, Davood Shishebori, Junfeng Ma, Sarah Entezari
Summary: During COVID-19, blood shortages occurred due to reduced donations, and optimising blood use through a reliable supply chain network becomes crucial. This study addresses the gap in existing research and proposes an efficient heuristic approach to solve the problem.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Operations Research & Management Science
Alireza Paeizi, Ahmad Makui, Mir Saman Pishvaee
Summary: Food waste and its proper management pose significant challenges in supply chain network management. This study proposes a comprehensive inventory-routing model that considers the value fluctuation of products over time and uses a multi-stage stochastic programming approach. By incorporating the randomness of market demands and the impacts of each period on the next, the model enables chain stores to make informed decisions in inventory management and distribution, resulting in cost savings.
RAIRO-OPERATIONS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Mansoureh Hasannia Kolaee, Armin Jabbarzadeh, Seyed Mohammad Javad Mirzapour Al-e-hashem
Summary: This paper presents a multi-objective group tourist planning problem that considers economic, environmental, and social dimensions simultaneously, aiming to balance the three objectives by minimizing total cost and environmental impacts while maximizing total collected prizes from tourists' interests.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Interdisciplinary Applications
Nohan Joemon, Melpakkam Pradeep, Lokesh K. Rajulapati, Raghunathan Rengaswamy
Summary: This paper introduces a smoothing-based approach for discovering partial differential equations from noisy measurements. The method is data-driven and improves performance by incorporating first principles knowledge. The effectiveness of the algorithm is demonstrated in a real system using a new benchmark metric.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhibin Lu, Yimeng Li, Chang He, Jingzheng Ren, Haoshui Yu, Bingjian Zhang, Qinglin Chen
Summary: This study proposes a new inverse design method using a physics-informed neural network to identify optimal heat sink designs. A hybrid PINN accurately approximates the governing equations of heat transfer processes, and a surrogate model is constructed for integration with optimization algorithms. The proposed method accelerates the search for Pareto-optimal designs and reduces search time. Comparing different scenarios facilitates real-time observation of multiphysics field changes, improving understanding of optimal designs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Luca Gasparini, Antonio Benedetti, Giulia Marchese, Connor Gallagher, Pierantonio Facco, Massimiliano Barolo
Summary: In this paper, a method for batch process monitoring with limited historical data is investigated. The methodology utilizes machine learning algorithms to generate virtual data and combines it with real data to build a process monitoring model. Automatic procedures are developed to optimize parameters, and indicators and metrics are proposed to assist virtual data generation activities.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Julia Jimenez-Romero, Adisa Azapagic, Robin Smith
Summary: Energy transition is a significant and complex challenge for the industry, and developing cost-effective solutions for synthesizing utility systems is crucial. The research combines mathematical formulation with realistic configurations and conditions to represent utility systems and provides a basis for synthesizing energy-efficient utility systems for the future.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Samuel Adeyemo, Debangsu Bhattacharyya
Summary: This work develops algorithms for estimating sparse interpretable data-driven models. The algorithms select the optimal basis functions and estimate the model parameters using Bayesian inferencing. The algorithms estimate the noise characteristics and model parameters simultaneously. The algorithms also exploit prior analysis and special properties for efficient pruning, and use a modified Akaike information criterion for model selection.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Abbasali Jafari-Nodoushan, Mohammad Hossein Dehghani Sadrabadi, Maryam Nili, Ahmad Makui, Rouzbeh Ghousi
Summary: This study presents a three-objective model to design a forward supply chain network considering interrelated operational and disruptive risks. Several strategies are implemented to cope with these risks, and a joint pricing strategy is used to enhance the profitability of the supply chain. The results show that managing risks and uncertainties simultaneously can improve sustainability goals and reduce associated costs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
T. A. Espaas, V. S. Vassiliadis
Summary: This paper extends the concept of higher-order search directions in interior point methods to convex nonlinear programming. It provides the mathematical framework for computing higher-order derivatives and highlights simplified computation for special cases. The paper also introduces a dimensional lifting procedure for transforming general nonlinear problems into more efficient forms and describes the algorithmic development required to employ these higher-order search directions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
David A. Linan, Gabriel Contreras-Zarazua, Eduardo Sanhez-Ramirez, Juan Gabriel Segovia-Hernandez, Luis A. Ricardez-Sandoval
Summary: This study proposes a parallel hybrid algorithm for optimal design of process flowsheets, which combines stochastic method with deterministic algorithm to achieve faster and improved convergence.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiaoyong Lin, Zihui Li, Yongming Han, Zhiwei Chen, Zhiqiang Geng
Summary: A novel GAT-LSTM model is proposed for the production prediction and energy structure optimization of propylene production processes. It outperforms other models and can provide the optimal raw material scheme for actual production processes.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangoz, Ali Mesbah, Fani Boukouvala, Fernando Lima, Antonio del Rio Chanona, Christos Georgakis
Summary: This paper provides a concise perspective on the potential of machine learning in the PSE domain, based on discussions and talks during the FIPSE 5 conference. It highlights the need for domain-specific techniques in molecular/material design, data analytics, optimization, and control.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hesam Hassanpour, Prashant Mhaskar, Brandon Corbett
Summary: This work addresses the problem of designing an offset-free implementable reinforcement learning (RL) controller for nonlinear processes. A pre-training strategy is proposed to provide a secure platform for online implementations of the RL controller. The efficacy of the proposed approach is demonstrated through simulations on a chemical reactor example.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hunggi Lee, Donghyeon Lee, Jaewook Lee, Dongil Shin
Summary: This study introduces an innovative framework that utilizes a limited number of sensors to detect chemical leaks early, mitigating the risk of major industrial disasters, and providing faster and higher-resolution results.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Sibel Uygun Batgi, Ibrahim Dincer
Summary: This study examines the environmental impacts of three alternative hydrogen-generating processes and determines the best environmentally friendly option for hydrogen production by comparing different impact categories. The results show that the solar-based HyS cycle options perform the best in terms of global warming potential, abiotic depletion, acidification potential, ozone layer depletion, and human toxicity potential.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
LaGrande Gunnell, Bethany Nicholson, John D. Hedengren
Summary: A review of current trends in scientific computing shows a shift towards open-source and higher-level programming languages like Python, with increasing career opportunities in the next decade. Open-source modeling tools contribute to innovation in equation-based and data-driven applications, and the integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to significantly accelerate progress, but long-term support mechanisms are still necessary.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Daniel Cristiu, Federico d'Amore, Fabrizio Bezzo
Summary: This study presents a multi-objective mixed integer linear programming framework to optimize the supply chain for mixed plastic waste in Northern Italy. Results offer quantitative insights into economic and environmental performance, balancing trade-offs between maximizing gross profit and minimizing greenhouse gas emissions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
