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A stomatal optimization model integrating leaf stomata-photosynthetic capacity regulation in response to soil water stress

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AGRICULTURAL WATER MANAGEMENT 2025年 308卷

作者： Liu, Yong Hu, Tiesong Zhu, Rui Chen, Qiuwen Zeng, Xiang Jing, Peiran Huang, Yifan Wuhan Univ State Key Lab Water Resources Engn & Management Wuhan 430072 Peoples R China Nanjing Hydraul Res Inst Natl Key Lab Water Disaster Prevent Nanjing 210098 Peoples R China Minist Water Resources Pearl River Water Resources Commiss Pearl River Water Resources Res Inst Guangzhou 510611 Peoples R China Wuhan Univ Sch Resource & Environm Sci Wuhan 430079 Peoples R China Sun Yat Sen Univ Sch Civil Engn Guangzhou 510275 Peoples R China

Leaf stomatal regulation of water-carbon exchange processes plays a crucial role in the water-carbon cycle. Uncovering the response mechanism of leaf gas exchange to soil water stress is challenging due to the complex effects of both the stomatal regulation ( i.e. , stomatal conductance, g s ) and non-stomatal regulation ( i.e. , photosynthetic carboxylation capacity, V-cmax25). Different from previous studies that achieved stomatal and nonstomatal regulation in stomatal optimization models by linearly simplifying or independently optimizing V-cmax25 , this study hypothesizes that V-cmax25 and g(s) are co-regulated by balancing intercellular CO2 concentration (C-i). By adjusting stomatal opening to minimize water-carbon cost, a stomatal optimization model (SRSC model) that integrates the synergistic regulation of gs and V-cmax25 was developed. Experimental and numerical results show that the SRSC model accurately reproduces the stomatal response to environmental changes, especially for the low soil water potential conditions ( Psi(soil) <-2 MPa) compared to the previous models, which increased the R-2 of g(s) , photosynthetic rate (A(n)), and Ci reaching 2.56 %, 1.97 %, and 9.04 %, respectively. Additionally, the SRSC model reasonably predicted a coordinated decline in g(s) and V-cmax25 and concurrently mitigated the classical models that simulate gs and leaf water potential responses deviating from the actual values under drought conditions. More importantly, the SRSC model revealed that experiencing drought and flooding stresses in rice improved intrinsic water use efficiency by increasing photosynthetic capacity. This study refines the application of the stomatal optimization model and enhances the mechanistic understanding of the stomatal optimization model to a certain extent.

关键词： optimization model Stomatal conductance Photosynthetic carboxylation capacity Drought Water use efficiency

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Oilfield sustainability and management:An optimization model for the reconstruction of oil and gas gathering systems based on potential location mining

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Petroleum Science 2025年第2期22卷 935-955页

作者： Jie Chen Wei Wang Wen-Yuan Sun Dong Li Yu-Bo Jiao National Engineering Laboratory for Pipeline Safety/MOE Key Laboratory of Petroleum Engineering China University of Petroleum (Beijing)

The carbon emissions and cost during the construction phase are significant contributors to the oilfield *** oilfields enter the late stage,the adaptability of facilities *** achieve sustainable development,oilfield reconstruction was usually conducted in discrete rather than continuous *** by economic and sustainability goals,a 3-phase heuristic model for oilfield reconstruction was developed to mine potential locations in continuous *** phase 1,considering the process characteristics of the oil and gas gathering system,potential locations were mined in continuous *** phase 2,incorporating comprehensive reconstruction measures,a reconstruction model was established in discrete *** phase 3,the topology was further adjusted in continuous ***,the model was transformed into a single-objective mixed integer linear programming model using the augmented ε-constraint *** experiments revealed that the small number of potential locations could effectively reduce the reconstruction cost,and the quality of potential locations mined in phase 1 surpassed those generated in random or grid *** studies showed that cost and carbon emissions for a new block were reduced by up to 10.45% and 7.21 %,*** reductions were because the potential locations mined in 1P reduced the number of metering stations,and 3P adjusted the locations of metering stations in continuous space to shorten the pipeline *** an old oilfield,the load and connection ratios of the old metering station increased to 89.7% and 94.9%,respectively,enhancing operation ***,recycling facilitated the diversification of reconstruction measures and yielded a profit of 582,573 ￥,constituting 5.56% of the total *** study adopted comprehensive reconstruction measures and tapped into potential reductions in cost and carbon emissions for oilfield reconstruction,offering valuable insights for future oilfield de

关键词： Oilfield reconstruction Sustainable development optimization model Potential location 3-phase heuristic model

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Collaborative distribution optimization model and algorithm for an intelligent supply chain based on green computing energy management

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COMPUTING 2024年第8期106卷 2521-2539页

作者： Cai, Lu Yan, Yongcai Tang, Zhongming Liu, Aijun Hubei Univ Educ Sch Management Wuhan 430205 Hubei Peoples R China Hubei Normal Univ Sch Econ Management & Low Huangshi 435002 Hubei Peoples R China

Collaborative distribution is the core of modern logistics, and the collaborative distribution centre is the physical location of distribution. This article aims to study the use of green computing energy management to promote a collaborative distribution optimization model and algorithm for an intelligent supply chain. A multiobjective genetic algorithm for energy management using green computing and a multiobjective hybrid genetic algorithm based on parallel selection methods are designed and implemented. A joint optimization model of VRP & VFP for logistics distribution is established. Collaborative system design and collaborative system operation inventory control issues are integrated. Considering uncertain demand, a multiobjective mixed-integer programming model of energy management using green computing is established to solve this problem. Experimental research shows that the optimal solution is found before the optimal operation of the 24th-generation collaborative system. The designed functional value of the collaborative system is 66109, and the optimal operating value of the collaborative system is 57348.

关键词： Smart supply chain Collaborative distribution optimization model Genetic algorithm

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Towards an efficient electric bus system: Multi-phase optimization model for incremental electrification of bus network with uncertain energy consumption

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2025年 173卷

作者： Davazdah, Behnam Zhang, Yiling Khani, Alireza Song, Ying Univ Minnesota Dept Civil Environm & Geoengn Minneapolis MN 55455 USA Univ Minnesota Dept Ind & Syst Engn Minneapolis MN USA Univ Minnesota Dept Geog Environm & Soc Minneapolis MN USA

Electrifying bus transit systems emerges as a practical solution to environmental degradation resulting from the unprecedented level of mobility nowadays. In the U.S., with the intensified efforts to expand EV infrastructure, a special emphasis is now placed on providing emission-free transit services. This initiative is central to America's push towards a net-zero-emissions future. In response, a growing number of cities have started replacing diesel buses with battery electric buses (BEBs). However, technological, operational, and economic barriers related to charging infrastructure and power supplies make the electrification of bus systems a gradual process, where only a part of the system is electrified at each stage. Moreover, due to the limited battery capacities of BEBs and their stochastic discharge rates influenced by factors like weather, traffic, and road conditions, BEBs often require daytime charging to be able to continue operating throughout the day. Therefore, transit agencies need to develop an integrated strategy that can address various costs of electrification and minimize the planning and operational costs. This study proposes a framework to facilitate the incremental electrification of bus systems. We formulate the problem as a two-stage stochastic mixed-integer linear programming model. The first stage optimizes long-term strategical decisions related to fleet sizing, charging station siting, and charging-station-route assignments under random BEB charging demand and time- of-use electricity tariffs. The second-stage optimizes the charging operations of the BEB fleet for a realized charging demand scenario while maintaining the service schedule for passenger convenience. We also develop a Benders decomposition method to solve the problem with better computational efficiency than existing solvers. To validate the proposed model, we test it on a real-world bus network to design an incremental electrification plan. We show the efficacy of the sol

关键词： Electric buses optimization model Charging infrastructure Charging station Stochastic model Electric transit system Transportation and sustainability Public transportation

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Capacity Estimation for Semiconductor Wafer Fabrication Facilities via an optimization model Based on Flexible Lead Times

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IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING 2025年第2期38卷 292-310页

作者： Hong, Sungwon Lee, Younsoo Lee, Kyungsik Seoul Natl Univ Dept Ind Engn Seoul 08826 South Korea Soongsil Univ Dept Ind & Informat Syst Engn Seoul 08826 South Korea

In this paper, we consider the problem of production capacity estimation for a semiconductor wafer fabrication facility. Capacity estimation involves determining the maximum achievable throughput of a wafer fabrication facility during a given planning horizon in consideration of both product mix and target cycle time. The wafer fabrication facility (fab) is one of the most complex production systems, consisting of hundreds of process steps for each product as well as thousands of processing machines and re-entrant process flows wherein products must visit the same workcenter multiple times. In this regard, estimating production capacity by modeling the wafer manufacturing process is a challenging problem. To properly capture the dynamics of the process, we propose a flexible-lead-time-based optimization model that considers both the state of work-in-process (WIP) over time and the relationship between WIP levels and lead times. The results of simulation experiments using a real-sized instance demonstrate the advantages of the proposed model over existing alternatives.

关键词： Production Semiconductor device modeling Capacity planning Fabrication Computational modeling Analytical models Estimation Integrated circuit modeling Data models Capacity estimation semiconductor manufacturing wafer fabrication flexible lead time optimization model optimization model

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Improving the healthcare user experience: an optimization model grounded in patient-centredness

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BMC HEALTH SERVICES RESEARCH 2025年第1期25卷 1-11页

作者： Peruzzo, Elisa Seghieri, Chiara Vainieri, Milena De Rosis, Sabina St Anna Sch Adv Studies Inst Management Management & Healthcare Lab Pisa Italy

BackgroundPatient satisfaction and experience are key outcomes of healthcare and can be computed as powerful measures of service quality. Understand what affects them is essential for service quality improvement. Investigating whether the care setting (i.e., medical or surgical) can impact the patients' perception of the quality can be also important for the actionability of this data. The aim is to explore which experiential factors should be prioritized to improve patient satisfaction with hospitalization service, using experience items as intermediate results and considering different ***-reported experience measures are used in an Italian region. This study uses the optimization approach to identify factors of healthcare user experience affecting and enhancing *** results confirm that, among the significant determinants of satisfaction, some specific experiential aspects emerged as the potential primary focus to be prioritized in improvement actions. These aspects vary according to the specific departmental *** study presents an optimization model directly informed by healthcare service users, utilizing their insights to drive healthcare delivery improvements. It emphasizes the necessity of not only collect patient perspectives but also applying different methodologies to understand what matters to patients and what interventions could be prioritized, and to strategically use diverse insights to enhance the delivery of healthcare services and patient experience and satisfaction.

关键词： Patient satisfaction Patient experience Hospitalization optimization model Healthcare service User-centricity Quality improvement

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Research on optimization model of Public Transport Dispatch Based on Combination Mode

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IEEE ACCESS 2024年 12卷 59665-59679页

作者： Chen, Shenjin Yuan, Junying Guangzhou Nanfang Coll Sch Elect & Comp Engn Guangzhou 510970 Peoples R China

To solve the conflict of interests between citizens' travel and public transportation enterprises, and alleviate the pressure of passenger flow at morning and evening peak bus stop, a multimodal combination optimization model for public transportation scheduling was proposed. Because the public transport enterprise adopted the conventional dispatching mode, there was a mismatch between passenger flow and transport capacity input. By establishing the public transport dispatching optimization model of the combination of the conventional bus and the inter-district bus, the conventional bus, and the large station express bus, solving the public transport dispatching algorithm, using the vehicle control method of the large passenger flow regional bus stop, we could obtain the control relationship of the arrival time of controllable vehicles. The experimental results show that the Combinatorial optimization scheduling of controllable vehicles enables controllable vehicles to reach the sixth station at the same time, the congestion cost of passengers on the vehicle is zero, and the waiting time of citizens is reduced by 11.15%, which can alleviate the congestion of citizens, improve the public transport capacity, and solve the travel problems of citizens.

关键词： Combination mode bus scheduling optimization model vehicle control controllable scheduling public transportation capacity

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A Feedback Mechanism With Unknown Bounded Confidence-Based optimization model for Consensus Reaching in Social Network Group Decision Making

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年第6期54卷 3357-3368页

作者： You, Xinli Hou, Fujun Shanxi Univ Sch Econ & Management Taiyuan 030006 Peoples R China Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China

Various feedback mechanisms focus on bounded confidence in the consensus reaching process (CRP) for group decision making (GDM) problems. However, confidence level from DMs' subjective cognition can lead to over-confidence, and thus to have negative effect on CRP. With this idea in mind, this article proposes an objective way to determine bounded confidence levels. In this article, the distribution linguistic preference relation (DLPR) is used to describe decision makers' (DMs') preferences on alternatives. A consensus reaching model with DLPRs in social network GDM (SNGDM) with bounded confidence effect is constructed. In the proposed consensus approach, the objective bounded confidence level is obtained from individual professional performance and social performance, i.e., knowledge degree based on consistency index and entropy measure of DLPRs, and the reliability degree based on trust degree received from other DMs. Then, the acceptable advices based on a bounded confidence-based optimization approach is provided for the identified DMs. Finally, a numerical example and comparative simulation analysis are provided to justify its feasibility and superiority.

关键词： Linguistics Social networking (online) Reliability Entropy Indexes optimization methods Decision making Bounded confidence consensus distribution linguistic preference relation (DLPR) optimization model social network group decision making (SNGDM)

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Thermal management of electric vehicle power cabin based on fast zero-dimensional integrating accurate three-dimensional optimization model

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APPLIED ENERGY 2025年 378卷

作者： Li, Peimiao Wang, Shibo Wang, Hui Feng, Yun Li, Hongliang Xiao, Heye Xi An Jiao Tong Univ Sch Energy & Power Engn MOE Key Lab Thermofluid Sci & Engn Xian 710049 Shaanxi Peoples R China Northwestern Polytech Univ Sch Aeronaut Xian 710072 Shaanxi Peoples R China COMAC Beijing Aircraft Technol Res Inst Beijing 102211 Peoples R China Northwestern Polytech Univ Unmanned Syst Res Inst Xian 710072 Shaanxi Peoples R China

The heat dissipation scheme design of power cabin is limited by complex configuration and slow iteration speed. Given the considerable time and computing resources required by numerical experiment, this work proposes a fast zero dimensional integrating accurate three-dimensional optimization model to calculate the heat dissipation and optimize the thermal management in electric vehicle power cabin. Based on the existing thermal equivalent circuit model, the heat capacity and thermal resistance network among each equipment is established in fast zero-dimensional model, and the output of fast zero-dimensional model is corrected by referring to the accurate initial three-dimensional simulation results. Then, the optimal heat dissipation configuration is searched by zero- dimensional model and validated by experimental data. Results show that the optimization result of fast zero dimensional integrating accurate three-dimensional optimization model is well verified by three-dimensional model. The chip temperature of the power cabin motor controller can be reduced from 551.73 K to 352.31 K after optimizing the number and size of the pin-fins of the motor controller using the proposed model. The time consumption of fast zero dimensional integrating accurate three-dimensional optimization model is 72.0872 h, while the time consumption of three-dimensional model is about 576 h with 224 cores of computer. The proposed model can be used to achieve the purpose of rapidly predicting the temperature change of the complex vehicle design, and provide theoretical reference for the reasonable formulation of the heat dissipation scheme.

关键词： Thermal management Electric vehicle Power cabin Zero and three dimensional integrating optimization model

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Cost and energy synergy optimization model for ironmaking processes: Hybrid knowledge and data driven

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JOURNAL OF CLEANER PRODUCTION 2025年 486卷

作者： Wang, Jiabao Zhang, Jianliang Wang, Yaozu Liu, Zhengjian Sun, Qingke Song, Xiaoran Li, Zhen Univ Sci & Technol Beijing Sch Met & Ecol Engn Dept Phys Chem 30th Xueyuan Rd Beijing 100083 Peoples R China Univ Sci & Technol Beijing Sch Intelligence Sci & Technol 30th Xueyuan Rd Beijing 100083 Peoples R China Univ Sci & Technol Beijing Inst Artificial Intelligence 30th Xueyuan Rd Beijing 100083 Peoples R China

Traditional ironmaking process optimization models mostly focus on the compositional properties of the product as constraints in order to optimize the material structure of the ironmaking process, and have not yet considered the influence of nonlinear quality factors on the dosage optimization scheme. In this paper, an integrated model coupling sinter ore quality performance to cost and energy co-optimization of the ironmaking process is proposed. A mathematical model for the whole-process batching of sinter and blast furnace was established by considering the material and energy flows, and a sinter ore quality prediction model was developed based on a data-based approach. With the lowest cost and energy consumption as the optimization objective, an improved genetic algorithm was used to solve the model and find the group of batching schemes that meet the conventional performance and quality indexes. At the same time to meet the conditions of the optimization scheme of a number of indicators for a comprehensive evaluation, to give to meet the requirements of the optimal program *** the optimization of the test, the cost and energy consumption per ton of iron of the optimal solution are reduced by 5.373 & YEN;/t and 2.129 kgce/t, respectively. Future optimization of the proportion of raw materials for ironmaking, taking into account quality factors, is an important step in the development of lowcarbon and low-cost, especially in the optimization of blast furnace production in the "black box" state.

关键词： Ironmaking optimization model Smart metallurgy Energy consumption and carbon reduction Integration of knowledge and data

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