Article
Computer Science, Interdisciplinary Applications
Dujuan Wang, Jian Peng, Hengfei Yang, T. C. E. Cheng, Yuze Yang
Summary: In this paper, a distributionally robust optimization model (DROM) is proposed for emergency logistics in disaster relief management. The model considers uncertain demand and facility disruptions, and describes their distributions through ambiguity sets. Based on the adaptability and tractability of the ambiguity sets, the model is reformulated as a mixed-integer linear program. An exact algorithm based on Benders decomposition (BD) is proposed to solve the model, along with an in-out Benders cut generation strategy to improve the efficiency.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Marine
Xinyang Xu, Haiyan Wang, Pengzhu Deng
Summary: With the rapid economic development and increasing demand for transport quality, there is renewed attention on multimodal transportation. However, unpredictable transport environments and uncertainties in market demand pose difficulties for transport decision-makers, hindering the development of multimodal transportation. This paper proposes a model for optimizing paths in multimodal transportation networks with uncertainties, using a genetic algorithm. The results show that synchromodal transportation can effectively respond to uncertainties and reduce transportation costs. This paper supports the introduction of synchromodal transportation, which is significant for the future development of multimodal transportation.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Yachao Zhang, Wei Liu, Zhanghao Huang, Feng Zheng, Jian Le, Shu Zhu
Summary: The advancement of dynamic wireless charging technology for electric vehicles has led to the development trend of electrified transportation systems, prompting the need for a coordinated operational model. A distributionally robust optimization (DRO) model is proposed to comprehensively address uncertainties in multi-energy coupled systems, resulting in cost savings and improved decision-making for system reliability and economy.
Article
Economics
Carlos Aller, Lorenzo Ductor, Daryna Grechyna
Summary: The study identifies GDP per capita, the share of fossil fuels in energy consumption, urbanization, industrialization, democratization, the indirect effects of trade, and political polarization as the robust determinants of CO2 emissions per capita. These determinants all negatively impact the environment except political polarization. Additionally, the determinants of CO2 emissions are found to vary depending on a country's level of income per capita.
Article
Green & Sustainable Science & Technology
Zahra Ziaei, Armin Jabbarzadeh
Summary: Carbon emission in transportation research has been widely studied, but research specifically on hazardous material transportation remains limited. This study presents a multi-objective model for locating transfer points and routing in a hazardous material multi-modal network, considering uncertainties and minimizing carbon emission, risk, and cost. The results confirm the effectiveness and robustness of the developed model, showing a reduction in carbon emissions and individuals at risk for each additional dollar spent.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Thermodynamics
Junjie Zhong, Yijia Cao, Yong Li, Yi Tan, Yanjian Peng, Lihua Cao, Zilong Zeng
Summary: A distributed synergistic model with min max-min robust optimization is proposed for a 3-block integrated energy system, which effectively handles multiple uncertainties and accelerates the solution process with the developed C&CG-AOP algorithm. The simulation results show that the constructed uncertainty set considering spatial-temporal correlation and symmetry can reduce operating costs.
Article
Energy & Fuels
Jianmiao Liu, Junyi Li, Yong Chen, Song Lian, Jiaqi Zeng, Maosi Geng, Sijing Zheng, Yinan Dong, Yan He, Pei Huang, Zhijian Zhao, Xiaoyu Yan, Qinru Hu, Lei Wang, Di Yang, Zheng Zhu, Yilin Sun, Wenlong Shang, Dianhai Wang, Lei Zhang, Simon Hu, Xiqun (Michael) Chen
Summary: This paper proposes a method to estimate and analyze urban passenger transportation carbon emissions based on sparse trip trajectory data, using Hangzhou as a case study. The results show that urban expressways have the highest hourly carbon emissions. The potential applications of the developed methods and platform in smart mobility management and green transportation policies are also discussed.
Article
Geosciences, Multidisciplinary
Margarita Choulga, Greet Janssens-Maenhout, Ingrid Super, Efisio Solazzo, Anna Agusti-Panareda, Gianpaolo Balsamo, Nicolas Bousserez, Monica Crippa, Hugo Denier van der Gon, Richard Engelen, Diego Guizzardi, Jeroen Kuenen, Joe McNorton, Gabriel Oreggioni, Antoon Visschedijk
Summary: This study introduces a postprocessing tool for assessing and managing uncertainty in different emitting sectors, establishing a link between emission inventories and observed CO2 concentrations through Earth system modelling and data assimilation, in order to better understand the sources, patterns, and trends of CO2 emissions.
EARTH SYSTEM SCIENCE DATA
(2021)
Article
Computer Science, Information Systems
Haochuan Zhang, Jie Han, Xiaojun Zhou, Yuxuan Zheng
Summary: Robust optimization is a method used to solve real-world optimization problems, but most methods suffer from high computational costs and poor convergence. To address these issues, an improved algorithm is proposed which uses a second-order Taylor series surrogate model to reduce computational costs, explores the whole search space using the state transition algorithm to strengthen convergence, and utilizes a preference-based selection mechanism to balance robustness and optimality. The proposed method is applied to seven examples and shows accurate and robust solutions with lower computational costs compared to other methods.
Article
Green & Sustainable Science & Technology
Umit Agbulut
Summary: The study forecasts CO2 emissions and energy demand in Turkey's transportation sector using machine learning algorithms, showing significant increases in both by 2050. The paper emphasizes the need for policymakers to establish various measures and challenges to mitigate energy consumption and emissions from the transportation sector.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2022)
Article
Computer Science, Interdisciplinary Applications
Van-Nam Hoang, Trung Pham, Sawekchai Tangaramvong, Stephane P. A. Bordas, H. Nguyen-Xuan
Summary: This paper presents a novel robust concurrent topology optimization method for the design of uniform/non-uniform porous infills under the accidental change of loads. The method directly models multiscale structures and seeks robust designs by simultaneously optimizing macro- and microscopic structures through the minimization of the weighted sum of the expected compliance and standard deviation.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Thermodynamics
Yingchao Dong, Hongli Zhang, Ping Ma, Cong Wang, Xiaojun Zhou
Summary: A novel hybrid robust-interval optimization (HRIO) framework is proposed in this study to address the uncertainties in demand response and renewable energy generation in integrated energy system (IES) planning. The framework integrates robust optimization and interval analysis to account for the uncertainties associated with renewable energy generation output and demand response. A constrained multi-objective transition algorithm is developed to solve the deterministic bi-objective optimization problem, with investment operation cost and robustness as the optimization objectives. Simulation results demonstrate the efficacy of the proposed HRIO method in coordinating the system's economy, robustness, and operation reliability, providing theoretical guidance and potential engineering applications for IES operators.
Article
Computer Science, Interdisciplinary Applications
Song Bai, Zhan Kang
Summary: The paper presents a robust topology optimization method for structures with bounded loads and spatially correlated material uncertainties. The method combines random structural loads with bounded nature and random field discretization to model uncertainties, with a focus on minimizing mean value and standard deviation of structural compliance. Numerical examples show that the proposed method results in structurally robust designs against uncertainties.
COMPUTERS & STRUCTURES
(2021)
Article
Computer Science, Interdisciplinary Applications
Matteo Pozzi, Giacomo Bonaccorsi, Hyunsun Alicia Kim, Francesco Braghin
Summary: Most manufacturing processes have process tolerances that affect component behavior and compliance with design requirements. This study presents a simple approach for conducting robust structural topology optimization in the presence of manufacturing uncertainties. It uses a computationally efficient boundary-perturbation technique to describe etching errors and does not require frequent re-initialization or mapping between etched and nominal structures. Additionally, it allows for dealing with spatially varying errors without increasing computational cost.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Economics
Jidong Kang, Tsan Sheng Ng, Bin Su, Alexandre Milovanoff
Summary: The electrification of light-duty passenger vehicles is crucial for reducing carbon emissions in the transport sector, and a novel model has been proposed to identify optimal pathways for emission reduction in this sector. The model shows that large deployment of electric vehicles is necessary to achieve emission reduction targets.
