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4th International Conference on Wireless Communications, Networking and Mobile Computing

作者： Li, Yu-hua Fan, Zhi-ping Chen, Xi Kang, Feng Northeastern Univ Sch Business Adm Shenyang Peoples R China

ISBN: (纸本)9781424421077

In order to find appropriate ventures for venture capitalists, this paper researches the match problem between ventures and venture capitalists through an intermediary. This paper gives six indexes for evaluating the satisfaction degree of venture capitalists and three indexes for evaluating the satisfaction degree of ventures. Then, according to the satisfaction degree of ventures and venture capitalists and the commission of an intermediary, it proposes a multi-objective optimization model and gives the corresponding solution to the model. Finally, a numerical example is given to show the feasibility and efficiency of the proposed model.

关键词： ventures venture capitalists match multi-objective optimization model satisfaction degree

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A multi-objective optimization model for sizing an off-grid hybrid energy microgrid with optimal dispatching of a diesel generator

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JOURNAL OF ENERGY STORAGE 2023年 68卷

作者： Premadasa, P. N. D. Silva, C. M. M. R. S. Chandima, D. P. Karunadasa, J. P. NSBM Green Univ Fac Engn Dept Elect Elect & Syst Engn Homagama Sri Lanka Univ Moratuwa Fac Engn Dept Elect Engn Moratuwa 10400 Sri Lanka

The paper presents a multi-objective optimization model for sizing and operating a hybrid energy system con-sisting of solar photovoltaic, wind energy, diesel generator, and battery storage. A new concept of optimizing the diesel generator loading percentage has been introduced. Also, the introduced battery management criteria will enable an adaptive operation hours of the diesel generator while regulating the battery state of charge. The proposed optimization model aims to minimize the total investment cost, operation & maintenance cost, and system's carbon emissions. The number of PV panels, number of wind turbines, rated diesel generator capacity, rated battery capacity, and optimal loading percentage of the diesel generator will be optimized. The multi-objective optimization will be done using the Genetic Algorithm using MATLAB software. Obtained results are presented in a Pareto optimal chart for better analysis. The fuel cost per day, the levelized cost of electricity, the diesel generator on hours, and the emission factor of the hybrid system have been determined for each optimal output. A comparison was carried out with a previously proposed study and found that the proposed method increases the lifetime of the diesel generator by 42.9%. The optimal loading percentage of the diesel generator is found to be 75%. The proposed optimization model reduced the total cost and carbon emissions of the hybrid energy system by 3.5% and 0.7%, respectively. The levelized cost of energy and the payback period of the proposed hybrid microgrid system are 0.16 USD/kWh and 8 years, respectively, which verify that the proposed system is economically feasible.

关键词： multi-objective optimization model Genetic algorithm Hybrid energy system Diesel generator Optimal loading Adaptive operation

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multi-objective optimization and simulation model for the design of distributed energy systems

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APPLIED ENERGY 2016年第Dec.15期184卷 1508-1516页

作者： Falke, Tobias Krengel, Stefan Meinerzhagen, Ann-Kathrin Schnettler, Armin RVVTH Aachen Univ Inst High Voltage Technol IFHT Schinkelstr 2 D-52056 Aachen Germany

In this paper, a multi-objective optimization model for the investment planning and operation management of distributed heat and electricity supply systems is presented. Different energy efficiency measures and supply options are taken into account, including various distributed heat and power generation units, storage systems and energy-saving renovation measures. Furthermore, district heating networks are considered as an alternative to conventional, individual heat supply for each building. The optimization problem is decomposed into three subproblems to reduce the computational complexity. This enables a high level of detail in the optimization and simultaneously the comprehensive investigation of districts with more than 100 buildings. These capabilities distinguish the model from previous approaches in this field of research. The developed model is applied to a district in a medium-sized town in Germany in order to analyze the effects of different efficiency measures regarding total costs and emissions of CO2 equivalents. Based on the Pareto efficient solutions, technologies and efficiency measures that can contribute most efficiently to reduce greenhouse gas emissions are identified. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： multi-objective optimization model Distributed energy system Evolutionary algorithm Generation planning Combined heat and power District heating network

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A multi-objective optimization model for Matching Ventures and Venture Capitalists

A Multi-objective Optimization Model for Matching Ventures a...

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The 4th International Conference on Wireless Communications, Networking and Mobile Computing(第四届IEEE无线通信、网络技术及移动计算国际会议)

作者： Yu-hua LI Zhi-ping FAN Xi CHEN Feng KANG School of Business Administration Northeastern University Shenyang China

关键词： ventures venture capitalists match multi-objective optimization model satisfaction degree

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Integrated optimization model to explore the green transformation of energy-intensive industrial parks from environmental-economic perspectives

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ENERGY 2025年 325卷

作者： Zhao, Yingying Wang, Shanshan Gao, Gengyu Wu, Yuhang Zhang, Ruiqin Zhengzhou Univ Sch Ecol & Environm Zhengzhou 450001 Peoples R China Henan Key Lab Environm Chem & Low Carbon Technol Zhengzhou 450001 Peoples R China Zhengzhou Univ Coll Chem Zhengzhou 450001 Peoples R China

Energy-intensive industrial parks (IPs) are facing significant environmental and resource challenges while driving economic growth. Their green and low-carbon transformation is crucial for regional ecological development. An integrated industry-energy-technology optimization model for green development of energy-intensive IP was developed, which incorporated multi-objective optimization, conservation supply curve and industrial symbiosis coupling models. The energy saving, carbon and air pollutant emission reduction potentials, material saving benefits and economic costs were quantified combining scenario analysis to explore the green development optimal pathway of the IP. A case study of IP-A demonstrated that the optimized scenarios significantly outperform the baseline scenario in energy saving and emission reduction (ESER). The integrated scenario is the most effective in reducing emissions, and the carbon peak target can be achieved by 2030. Compared to the baseline scenario, the carbon emission reduction of integrated scenario is 15.5 Mt (65 % reduction rate) in 2035, and the SO2, NOx, and PM10 emission reduction rates range from 68 % to 74 %. Additionally, potential waste symbiosis activities in IP-A can generated significant material savings of 16787.6 kt in 2035. The results also indicated that high initial investment costs restrict the widespread promotion of structural adjustment measures that possess substantial ESER potential. Overall, waste heat recovery and energy efficiency technology promotion are effective mitigation paths in the short term. Industrial structure optimization and clean energy substitution are main driving factors for ESER in the long term.

关键词： Energy-intensive industrial park Industry-energy-technology integrated optimization multi-objective optimization model Green and low-carbon transformation path Environmental-economic analysis

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multi-objective optimization-based acoustic emission damage location in orthotropic steel decks considering complex wave paths

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ENGINEERING STRUCTURES 2025年 330卷

作者： Nie, Jia-Hao Li, Dan Wang, Hao Yu, Tao Kuang, Kevin Sze Chiang Southeast Univ Key Lab C&PC Struct Minist Educ Nanjing 211189 Peoples R China Southeast Univ Sch Civil Engn Nanjing 211189 Peoples R China Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore

Acoustic emission (AE) monitoring of orthotropic steel decks (OSDs) provides great potential for intelligent operation and maintenance of bridges, while accurate and efficient damage location in OSDs remains challenging due to its complex thin-walled spatial geometries. Considering the multi-solution problem induced by multiple wave propagation paths, a multi-objective optimization location model with two functional layers is presented, which includes the first objective function formulated on a traditional optimization-based method and a new objective function established on modal analysis. The hierarchical optimization strategy is introduced to obtain the unique solution of damage coordinate. Experiment on a full-scale OSD specimen demonstrated the enhanced capability of the proposed method in locating damage sources originating from both deck plate and U-rib more accurately, with a substantial reduction in mean geodesic distance errors from 123 mm and 73 mm to 49 mm over the traditional optimization-based method and the counterpart method without hierarchical optimization strategy.

关键词： Orthotropic steel decks Damage location Acoustic emission multi-objective optimization model Complex wave propagation paths Modal analysis

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optimization of a wind-PV-hydrogen production coupling system considering economy, environment, and reliability

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 105卷 441-457页

作者： Zhang, Xingyin Zhang, Huan Zhang, Libo Du, Lin Wang, Qunwei Zhou, Dequn Nanjing Univ Aeronaut & Astronaut Res Ctr Soft Energy Sci Nanjing 211106 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing 211106 Peoples R China Soochow Univ Sch Polit & Publ Adm Suzhou 215123 Peoples R China

Wind and photovoltaic (PV) coupled hydrogen production has gradually become one of the effective ways to cope with the intermittency and volatility of wind and PV power generation, promoting the utilization of their generated power. However, the current wind-PV-hydrogen coupling system mainly focuses on electricity-to- hydrogen conversion, while hydrogen-to-electricity conversion, especially for bidirectional electricity- hydrogen-electricity closed-loop systems, urgently requires in-depth research. In addition, although previous studies have incorporated fuel cell equipment, research on its costs and future development potential remains insufficiently explored. Moreover, the reliability requirements of system hydrogen production are rarely taken into account in multi-objective optimization. In this regard, this study proposes a coupling system that integrates wind power, PV power, electrolyzer equipment, hydrogen storage equipment, and hydrogen fuel cell equipment. The system enables hydrogen production, storage, co-generation, and bidirectional conversion between electricity and hydrogen. Subsequently, a multi-objective capacity configuration optimization model for the coupling system is constructed, aiming to maximize economic benefits, and minimize carbon dioxide emissions and fluctuations in electrolytic power. Then as a case study in Northwest China, employing a multi-objective Grey Wolf Optimizer (MOGWO) algorithm to solve the model and determine the optimal capacity configuration of the system. The results show that the system has a power abandonment rate of 1.33%, with an economic benefit of approximately 92,000 yuan, carbon dioxide emissions of about 19,000 kg, and electrolysis power fluctuations of around 2,800,000 kW2. In subsequent discussions and analysis, the study found that integrating hydrogen fuel cells into the coupled system effectively reduces reliance on external grids, which is of significant importance for achieving carbon reduction goals. F

关键词： Wind power PV power Hydrogen multi-objective optimization model MOGWO algorithm

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Equity-Oriented multi-objective optimization Allocation Strategies for Urban Water Resources

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WATER 2025年第4期17卷 557-557页

作者： Zhou, Shicheng Wang, Dong Liu, Zhen Ma, Yongqiang Liu, Xin Hebei Univ Engn Sch Informat & Elect Engn Handan 056038 Peoples R China

Urban water usage spans diverse sectors, requiring effective management strategies to address increasing demand, limited supplies, and sector-specific needs. In this study, a multi-objective urban water resource allocation model is proposed to balance economic, ecological, and social benefits, focusing on social fairness. The model considers water availability, demand diversity, and environmental factors for optimized resource allocation. An improved zebra optimization algorithm-based multi-objective evolutionary algorithm (ZOA-MOEA/D) is developed, integrating zebra optimization with a decomposition-based approach to overcome the traditional methods' limitations, improving solution diversity and convergence. ZOA-MOEA/D consistently outperforms the NSGA-II, MOPSO, and MOEA/D algorithms in solution distribution, convergence, quality, and diversity across multiple test scenarios. By applying the model to Ningbo, China, key trade-offs between economic growth, social fairness, living standards, and ecological protection are revealed. These findings provide useful insights into urban water resource management, offering a flexible framework for balancing multiple objectives and supporting sustainable development. Despite some limitations, the approach can contribute to the ongoing development of urban water resources.

关键词： urban water resource management multi-objective optimization model fairness in resource allocation zebra optimization algorithm-based multi-objective evolutionary algorithm HyperVolume indicator

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An Integrated MCDM-Based Mathematical modeling Approach for Sustainable Practices of Vermicomposting in Educational Institutions

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PROCESS INTEGRATION AND optimization FOR SUSTAINABILITY 2025年第2期9卷 575-592页

作者： Bhakuni, Mayank Singh Das, Utpal Bhakuni, Pooja Ramesh Kumar, S. Das, Amrit Dayananda Sagar Univ Sch Engn Dept Math Bengaluru 562112 India Vellore Inst Technol VIT Sch Agr Innovat & Adv Learning VAIAL Dept Hort & Food Sci Vellore 632014 Tamil Nadu India Jain Dept Comp Sci & Informat Technol Bengaluru 560069 India Vellore Inst Technol Sch Adv Sci Dept Math Vellore 632014 Tamil Nadu India

Vermicomposting, a bioconversion process that uses earthworms to decompose organic waste, has emerged as an eco-friendly solution for producing nutrient-rich compost. Despite its potential sustainability benefits, many educational institutions hesitate to adopt vermicomposting due to high costs and limited expertise. In educational institutions, where waste management and sustainability are critical, implementing efficient vermicomposting systems is essential. This study addresses this gap by proposing an integrated approach that combines the technique for order preference by similarity to the ideal solution (TOPSIS) with mathematical modeling to optimize the setup cost and production time of vermicompost plants. The multi-objective optimization model is solved using the neutrosophic compromise programming approach (NCPA) and inherent uncertainties efficiently captures through an advanced uncertain tool using trapezoidal neutrosophic number. Key components of the study include detailed criteria selection via TOPSIS and validation through a real-life case study at VIT Vellore. The study demonstrates optimal cost and time objective function values of 16,673 and 6036 units, respectively. The findings underscore a strong commitment to promote sustainable practices, significantly contributing to waste reduction, enhancing soil enrichment, and fostering environmental stewardship.

关键词： Vermicomposting multi-criteria decision making multi-objective optimization model TOPSIS Trapezoidal neutrosophic number Neutrosophic compromise programming

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Application of mixed integer programming and simulated annealing algorithm in sustainable logistics network design

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JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年

作者： Wang, Nana Liaoning Univ Int Business & Econ Sch Liberal Educ 33 Shunle St Dalian City 116052 Liaoning Provin Peoples R China

This article integrates mixed integer programming and the simulated annealing algorithm to enhance both the economic efficiency and environmental sustainability of logistics networks. A multi-objective optimization model is first developed, incorporating economic costs, carbon emissions, and social service levels to address the diverse needs of stakeholders. A solution approach combining the precision of mixed integer programming with the global search capabilities of the simulated annealing algorithm is then proposed. This hybrid approach effectively overcomes the limitations of traditional optimization methods, particularly in managing complex constraints and large-scale problems. Through practical case studies, the proposed method demonstrated superior optimization performance. The average total cost after optimization was $52,444.61, outperforming solutions derived from using either mixed integer programming or simulated annealing alone. Furthermore, the service satisfaction rate exceeded 90%, indicating the model's effectiveness in balancing multiple objectives. The findings of this study not only offer a novel theoretical framework for logistics network design but also provide valuable support for enterprises striving to achieve sustainable development in their operations. The research highlights the potential to strike a harmonious balance between economic, environmental, and social responsibilities, paving the way for more sustainable and efficient logistics practices.

关键词： sustainable logistics network design mixed integer programming simulated annealing algorithm multi-objective optimization model environmental friendliness

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