Article
Green & Sustainable Science & Technology
Ha-Jun Yoon, Seung-Kwon Seo, Chul-Jin Lee
Summary: Establishing hydrogen infrastructure is crucial for achieving a hydrogen economy. This study used mixed-integer linear programming to minimize the cost of the hydrogen supply chain, including the utilization of byproduct hydrogen and natural gas pipelines. The results showed that utilizing existing infrastructure can significantly reduce the cost of hydrogen and provide economic benefits for optimizing the hydrogen supply chain.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Computer Science, Interdisciplinary Applications
Camilo Lima, Susana Relvas, Ana Barbosa-Povoa
Summary: This paper investigates the strategic and tactical planning of a downstream oil supply chain using a mixed-integer linear programming (MILP) model and chance constrained programming with fuzzy parameters to handle uncertainty. The proposed model aims to determine network design and product distribution plan cost-effectively, and has been validated through a real case study in the Brazilian oil industry, demonstrating its value in decision-support for real-life problems.
COMPUTERS & CHEMICAL ENGINEERING
(2021)
Article
Engineering, Industrial
Tadeusz Sawik, Bartosz Sawik
Summary: This paper applies stochastic optimisation of CVaR to maintain risk-averse viability and improve resilience of a supply chain under propagated disruptions. Two stochastic optimisation models are developed with conflicting objectives, and a stochastic mixed integer quadratic programming model is used to select a risk-averse viable production trajectory. The proposed approach is applied to smartphone manufacturing, and the findings show that more risk-aversive decision-making leads to a larger viability space and higher resilience of the supply chain. Single-objective decision-making may reduce supply chain viability.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Chemistry, Multidisciplinary
Ayeon Kim, Heehyang Kim, Hyunjun Lee, Boreum Lee, Hankwon Lim
Summary: This study uses mixed-integer linear programming to optimize the hydrogen supply chain for South Korea, recommending the import of blue hydrogen from Qatar and Russia, as well as green hydrogen from UAE and India, in the near term. The share of blue hydrogen dominates initially but is expected to be gradually replaced by green hydrogen as renewable electricity prices decrease.
ACS SUSTAINABLE CHEMISTRY & ENGINEERING
(2021)
Article
Chemistry, Physical
Mehmet Guray Guler, Ebru Gecici, Ahmet Erdogan
Summary: This study investigates the design of Turkey's hydrogen supply chain to minimize total cost while meeting the demand of the transportation sector. Using a mixed integer programming model, insights for the future hydrogen supply chain are derived, including the importance of decentralization and the coordination of hydrogen production and import.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2021)
Article
Agricultural Engineering
Santosh Nandi, Vinay Gonela, Iddrisu Awudu
Summary: The paper assesses the feasibility of establishing a large-scale supply chain of bioethanol based on regional availability of agricultural residues. It proposes a bioethanol supply chain model and conducts comparative analyses and sustainability assessments. The findings suggest different sustainable configurations for different agricultural residues.
BIOMASS & BIOENERGY
(2023)
Article
Thermodynamics
Fiona Clarke, Bogdan Dorneanu, Evgenia Mechleri, Harvey Arellano-Garcia
Summary: This paper presents a mixed integer linear programming model for the optimal design of a distributed energy resource (DER) system that meets electricity, heating, cooling and domestic hot water demands of a neighbourhood. The focus is on the design, interaction and operation of the pipeline network, considering operation and maintenance costs. The scalability of the model is tested by applying it to neighbourhoods of different sizes.
Article
Engineering, Biomedical
Gehan Abouelseoud, Yasmine Abouelseoud, Amin Shoukry, Nour Ismail, Jaidaa Mekky
Summary: This paper aims to develop a rigorous mathematical framework, based on mixed integer programming, for the analysis of the cortical vision prosthesis design problem and the optimal estimation of a prosthesis setup parameters. The simulated examples illustrate the unique capabilities of the proposed strategy in testing the feasibility of the goals of a prosthesis under a set of specified design constraints. Future research should focus on how these electrodes can be safely implanted, and once this is possible, the proposed framework can be applied to decide their optimal locations and excitation currents.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Computer Science, Interdisciplinary Applications
Mohammadmahdi Alizadeh, Behrooz Karimi
Summary: The research aims to design and plan a downstream oil supply chain network under mixed uncertainty. A bi-objective mixed-integer linear model is proposed to make decisions at tactical and strategic levels. To deal with mixed uncertainty, a hybrid uncertain programming approach is developed and applied. The implementation of the proposed model in a real-life case leads to improved network performance and cost reduction against operational and disruption risks.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Operations Research & Management Science
Yang Xia, Wenjia Zeng, Xinjie Xing, Yuanzhu Zhan, Kim Hua Tan, Ajay Kumar
Summary: This study explores the implementation of a blockchain-enabled fleet sharing solution to optimize drone operations. By using blockchain, transparency and security can be provided, allowing equal access to shared resources for all participants. The problem, which involves multiple objectives and varying levels of sharing abilities, is solved using a mixed-integer programming model and a tailored algorithm. Extensive experiments demonstrate the computational performance of the proposed solution and the effectiveness of using blockchain to improve overall optimization. Several critical influential factors with managerial significance are also highlighted.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Operations Research & Management Science
Xin Cheng, Xiang Li
Summary: This paper introduces a method based on discretization and mixed-integer linear programming relaxations for global optimization of mixed-integer bilinear programs. By proposing new discretization formulations and an adaptive discretization global optimization algorithm, better computational efficiency and solution quality are achieved.
JOURNAL OF GLOBAL OPTIMIZATION
(2022)
Article
Chemistry, Physical
Ahmet Erdogan, Ebru Gecici, Mehmet Guray Guler
Summary: Hydrogen fuel cell vehicle (HFCV) technology is an important alternative to conventional fossil fuel vehicles in the transportation sector. However, the hydrogen supply chain (HSC) infrastructure poses a significant obstacle to their widespread use. This study proposes an HSC design for Turkey that minimizes cost, carbon emissions, and security risks. The problem is modeled using mixed integer linear programming (MILP), and five different optimization cases are studied.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Chemistry, Multidisciplinary
Linh Thi Truc Doan, Yousef Amer, Sang-Heon Lee, Phan Nguyen Ky Phuc, Tham Thi Tran
Summary: This study proposes an e-waste RSC model that considers fuzzy parameters and risk factors, solved through crisp transformation, allowing decision-makers to choose solutions based on their satisfaction, achieving a compromise between constraint satisfaction and objective value.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Ilker Karadag, Muhammed Emre Keskin, Vecihi Yigit
Summary: This research presents a novel multi-objective mixed-integer location-allocation model for a blood supply chain design problem, which effectively plans a supply chain network consisting of mobile and permanent units. By prioritizing objectives using the Analytical Hierarchical Process, the model minimizes distances between blood supply chain elements and the length of mobile unit routes. Empirical results show that the proposed model offers at least 25% more effective solutions compared to the current situation.
Article
Energy & Fuels
Cormac O'Malley, Patrick de Mars, Luis Badesa, Goran Strbac
Summary: Decarbonisation is driving the growth of renewable power generation and increasing uncertainty in power plant scheduling. This paper compares traditional mathematical programming methods with emerging reinforcement learning methods, finding that the former is more reliable and scalable with lower costs. However, the strength of reinforcement learning lies in its ability to produce instant solutions.
Article
Computer Science, Information Systems
Yuhao Yao, Haoran Zhang, Defan Feng, Jinyu Chen, Wenjing Li, Ryosuke Shibasaki, Xuan Song
Summary: This study analyzed the modifiable areal unit problem of the error in crowd density estimation from big mobility data. An optimization model-based restoration method was proposed by regarding the error as the result of a convolution operation, and the restoration effect was analyzed under different circumstances through several simulation experiments. A real application for grided population distribution map construction and restoration from Call Detail Record was conducted to prove the reliability of the whole analysis, which demonstrated that the restoration method can reduce the error by nearly 40% under certain conditions.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Engineering, Multidisciplinary
Peiran Li, Haoran Zhang, Wenjing Li, Keping Yu, Ali Kashif Bashir, Ahmad Ali Alzubi, Jinyu Chen, Xuan Song, Ryosuke Shibasaki
Summary: Tracking demographic dynamics is important for smart city development. We proposed a reliable approach based on the Industrial Internet of Things to track the demographic dynamics in the built environment, and inferred demographic data based on life-pattern features.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Chemistry, Multidisciplinary
Baikang Zhu, Qinbing Dong, Jianghua Huang, Debin Song, Lihui Chen, Qingguo Chen, Chunyang Zhai, Bohong Wang, Jiri Jaromir Klemes, Hengcong Tao
Summary: A polymer-assisted synthesis strategy was used to create a polymorph-controlled alpha-Bi2O3/Bi2O2CO3 heterojunction, which improved the efficiency of photocatalytic degradation of tetracycline pollutants. The p-n heterojunction effectively separated and migrated electron-hole pairs, leading to a high removal efficiency of 98.21% for tetracycline degradation within 1 hour. The study also identified the primary active species and intermediate products involved in the photocatalytic oxidation reactions.
Article
Green & Sustainable Science & Technology
Keyong Zhang, Sulun Li, Peng Qin, Bohong Wang
Summary: In the context of digital economy and low carbon economy, digital technology plays a crucial role in achieving carbon peaking and carbon neutrality. A study based on the panel data of 30 Chinese provinces from 2011 to 2019 found that digital technology development has a positive impact on reducing carbon emissions in the region in both the short term and long term. However, the spatial spillover effect of digital technology on carbon emissions in neighboring regions is not significant. Policy makers should consider spatial effects when promoting the application of digital technologies in environmental governance.
Article
Engineering, Environmental
Jianghua Huang, Baikang Zhu, Debin Song, Bohong Wang, Lihui Chen, Lu Lu, Qingguo Chen, Limei Gai, Chunyang Zhai, Li Chen, Hengcong Tao
Summary: A novel Bi2S3/CeVO4 S-scheme heterojunction photocatalyst was prepared by solvent thermal method. The construction of S-scheme heterostructure facilitated the separation and migration of photogenerated carriers, resulting in excellent redox capacity and efficient production of free radicals. The optimized Bi2S3/CeVO4 heterojunction showed high degradation efficiency for naphthalene in both pure water and simulated seawater.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Engineering, Chemical
Jianqin Zheng, Jian Du, Yongtu Liang, Bohong Wang, Miao Li, Qi Liao, Ning Xu
Summary: To improve the transport of different oil products and minimize contamination, a hybrid intelligent framework is proposed to track the real-time batch interface of multi-product pipelines. The framework includes a batch injection judgment module and a volume calculation model to accurately determine the location of each batch interface. A self-learning modified model is also introduced to compensate for tracking errors. The proposed model is verified using a real-world multi-product pipeline network in China and shows better performance compared to other methods.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2023)
Review
Energy & Fuels
Xianlei Chen, Manqi Wang, Bin Wang, Huadong Hao, Haolei Shi, Zenan Wu, Junxue Chen, Limei Gai, Hengcong Tao, Baikang Zhu, Bohong Wang
Summary: The oil & gas transport and storage engineering is exploring ways to reduce energy consumption and carbon footprints by connecting each part through supply chains. This study provides an overview of current methods, technological improvements, and the latest trends in OGTS to achieve sustainable development goals. The critical analyses focus on increasing flexibility, energy saving, emission reduction, and changing energy structure. The study emphasizes the need for further improvement in energy efficiency, reducing energy/water/material consumption and emissions, and maintaining safety in the extensive oil & gas network.
Article
Thermodynamics
Qing Yuan, Yuyao Gao, Yiyang Luo, Yujie Chen, Bohong Wang, Jinjia Wei, Bo Yu
Summary: In this study, a general operation optimization model with the optimal goal of minimum energy cost is established for a heated oil pipeline system considering mixed discrete-continuous decision variables and complex constraint conditions. An intelligent optimization method combining the hybrid binary-real-coded genetic algorithm (BRCGA) and the penalty method coupled with the simulation of a heated oil pipeline system is proposed to solve the optimization model. The optimization model and solution method are applied to the operation optimization of a complex actual heated oil pipeline system, and an optimal operation scheme is intelligently determined, resulting in a significant saving of 18.7% in energy cost.
Article
Thermodynamics
Yifan Xu, Mengmeng Ji, Jiri Jaromir Klemes, Hengcong Tao, Baikang Zhu, Petar Sabev Varbanov, Meng Yuan, Bohong Wang
Summary: This paper investigates the economic viability of transforming renewable energy into exportable electricity or hydrogen. A comprehensive renewable energy system model is developed based on the P-graph to simulate an energy system that integrates electricity, heat, and hydrogen on a virtual island. Findings from the case study show that exporting extra renewable energy by electricity is cheaper than using hydrogen for the studied island, and the optimal dispatch structure can deliver 51 GWh of electricity annually for 292 M CNY (about 42 M EUR). A sensitivity analysis of export prices and renewable energy uncertainty verifies the economics of electricity export.
Article
Energy & Fuels
Xiaojuan Hu, Yunqian Long, Gong Xuan, Yuyi Wang, Xiaohe Huang, Yupeng Xu, Jing Liu, Bohong Wang, Fuquan Song
Summary: In this study, a novel Pickering emulsion stabilized by magnetic nanoparticles Fe3O4@PDA@Si was designed and prepared. The emulsion showed excellent stability and inhibition of demulsification, making it a potential option for enhanced oil recovery.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Thermodynamics
Lianghui Guo, Yi Wang, Yuejiu Liang, Bohong Wang
Summary: The heat exchange network is an important energy recovery unit in chemical processes. This article proposes an optimization method, which includes a Temperature Zone Diagram (TZDM), and a mathematical programming model, to present the optimization results through solving the model. An energy representation method of the stream temperature-energy diagram (STED) is also established. The example shows that the optimized heat transfer recovery of this method is 1.12MJ, which is 10.42% higher than the traditional Pinch Analysis-based approach. This method has good adaptability and can solve the complex optimization problem of heat exchange networks in natural gas purification plants, etc.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2023)
Article
Thermodynamics
Yu-Jie Chen, Dongliang Sun, Bo Yu, Bohong Wang, Wei Lu, Wei Zhang
Summary: This paper proposes a horizontal refined piecewise linear interface reconstruction (HOPLIRE) method for the numerical research of two-phase problems in incompressible flow. The method reconstructs the two-phase interface within one grid cell using multiple horizontal refined pieces, making implementation straightforward and allowing easy computation of the volume fraction flux for solving the VOF function. The HOPLIRE method not only has a simple implementation but also achieves high accuracy in reconstructing the vapor-liquid interface. The performance of the VOSET-HOPLIRE method is verified through comparisons with other popular methods, demonstrating good accuracy and efficiency. Further improvements to extend the method to three-dimensional problems and unstructured meshes are expected in the future.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2023)
Article
Engineering, Civil
Xiaodan Shi, Haoran Zhang, Wei Yuan, Ryosuke Shibasaki
Summary: In order to achieve long-term trajectory prediction for pedestrians in crowds, we propose a general framework that allows prediction models to transfer well to unseen scenes and objects by quickly learning prior information of trajectories. This framework utilizes carefully designed sub-tasks and meta-tasks to learn trajectory information related to scenes and objects, resulting in accurate long-term future prediction.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Jinyu Chen, Xiaodan Shi, Haoran Zhang, Wenjing Li, Peiran Li, Yuhao Yao, Satoshi Miyazawa, Xuan Song, Ryosuke Shibasaki
Summary: Monitoring the crowd in urban hotspots is a crucial research topic in urban management with significant social impact. This study proposes a confirmed case-driven time-series prediction model named MobCovid to forecast the crowd in urban hotspots, considering both the number of nighttime staying people and confirmed COVID-19 cases. The effectiveness of the proposed method is validated through multiple comparisons with other baselines.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Engineering, Civil
Zengxian Li, Aijun Liu, Wen-Long Shang, Jiaxin Li, Hui Lu, Haoran Zhang
Summary: This paper presents an innovative fuzzy group decision-making model for assessing regional transportation sustainability, with a focus on evaluating the correlation between different attributes in the evaluation system. The study introduces a partitioned Maclaurin symmetric mean operator which proves to be more applicable in handling attribute correlation and grouping. Furthermore, a modified spherical fuzzy partitioned Maclaurin symmetric mean operator is proposed, expanding its application scope. Weight vectors for attributes and experts are obtained using the extended statistical variance method and evidence-based Bayes approximation method. The research also develops a fuzzy assessment model for sustainable transportation and demonstrates its feasibility and universality through a numerical example and comparison with previous studies.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Chemical
Andrea Coletto, Pietro Poesio
Summary: Experiments and simulations were conducted to study the air volume fraction and hold-up in a bubble channel reactor. A new signal processing method was proposed to avoid the loss of bubble residence time. The results were in agreement with previous studies and a bubble-scale model was developed to explain the relationship between hold-up and air superficial velocity.
CHEMICAL ENGINEERING RESEARCH & DESIGN
(2024)
