Article
Green & Sustainable Science & Technology
Linqi Li, Hongwu Zhang
Summary: The model integrates various approaches for handling uncertainties, including inexact stochastic programming and fuzzy random intervals, to address multiple objectives in optimal sediment allocation. Through empirical validation, the model has shown effective reduction in sedimentation in water channels and improved efficiency in sediment utilization.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Industrial
Limao Zhang, Penghui Lin
Summary: This paper proposes a hybrid approach integrating ensemble learning and genetic algorithm for optimizing limit support pressure and ground surface deformation during tunnel excavation, considering uncertainties from geological conditions and meta-models. The method achieves an improved design by conducting multi-objective optimization and selecting the best solution based on the shortest distance from the ideal point.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Energy & Fuels
Sudlop Ratanakuakangwan, Hiroshi Morita
Summary: This study proposes a combination of multi-objective optimization and efficiency measurement for determining an efficient energy mix in energy planning. It considers various dimensions of energy planning and associated uncertainties. The proposed model includes multiple objective functions related to energy need, cost, environmental impact, security, social impact, and social benefit. The slacks-based measure methodology is applied to identify the best energy mix. The results show significant improvements in reducing emissions and dependence on certain power plant types, increasing employment and the proportion of electricity generated from renewable sources, with slight tradeoffs in costs. The quantitative results from the model can assist policymakers in efficiently determining an energy policy that optimizes various aspects under given constraints and scenarios of uncertainty.
Article
Automation & Control Systems
Xiaodong Sun, Zhou Shi, Gang Lei, Youguang Guo, Jianguo Zhu
Summary: This article introduces a new multilevel optimization strategy for efficient multiobjective optimization of an IPMSM. By using Pearson correlation coefficient analysis and cross-factor variance analysis, a three-level optimization structure is obtained based on the correlations of design parameters and optimization objectives. The use of Kriging model to approximate finite element analysis improves optimization efficiency and provides better design solutions.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Green & Sustainable Science & Technology
Zhixing Li, Yukai Zou, Huijuan Xia, Chenxi Jin
Summary: Less attention has been paid to the comfort and greenhouse gas emissions in old communities in current research. This study proposes strategies for improving the thermal environment comfort and reducing carbon emissions in low-and medium-rise old communities based on optimization in five typical Chinese cities. Parametric simulation and data collection methods are employed, and the relationship between design variables and environmental objectives is explored. The results show that the comfort of indoor and outdoor environments can be greatly improved, while carbon emissions can be reduced.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Electrical & Electronic
Mengyu Ma, Chao Wang, Zuxing Li, Geyong Min
Summary: This article investigates the efficient transmission design problem in a typical vehicle-to-vehicle (V2V) communication network, where multiple source-destination pairs with different types of message transmission requirements coexist and the network environment dynamically changes. A sequential transmission decision framework based on the multi-objective optimization (MOO) theory is proposed to maximize the performance of each link, while ensuring the QoS of different messages.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Article
Environmental Sciences
Ahmad Aman Jalili, Mohsen Najarchi, Saeid Shabanlou, Reza Jafarinia
Summary: This study combines the NSGA-II multi-objective algorithm with the WEAP simulator model to optimize reservoir operation and achieve the optimal policies of water resources systems in real time. The results demonstrate the efficiency of this method in predicting the optimal pattern of the dam rule curve based on new data of the inflow to the dam.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Mechanics
Parviz Mohammad Zadeh, Mostafa Mohagheghi
Summary: This paper presents an efficient multi-objective reliability-based design optimization method for composite structures, utilizing a hybrid decomposing-based algorithm and bi-level modeling strategy with both reliability and weight as objective functions. Demonstrated using laminated composite plate and benchmark problems, the proposed method shows computational efficiency and accuracy in evaluating the design performance of composite structures.
COMPOSITE STRUCTURES
(2022)
Article
Construction & Building Technology
Wu Zheng, Zhonghe Shui, Zhengzhong Xu, Xu Gao, Shaolin Zhang
Summary: This study presents a multi-objective optimization framework for optimizing concrete mixture proportions. Advanced methods such as K-fold cross-validation, Bayesian hyperparameter optimization, regression feature elimination, and C-TAEA algorithm are used to develop suitable machine learning models. The results show that the application of 5-fold cross-validation, hyperparameter optimization, and regression feature elimination significantly improve the prediction accuracy of compressive strength and binder intensity. The proposed MOO model with CTAEA algorithm exhibits high prediction accuracy and the ability to solve multi-objective mixture optimization problems, with errors between predicted and tested values around 4%.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Environmental Sciences
Linyuan Leng, Haifeng Jia, Albert S. Chen, David Z. Zhu, Te Xu, Shen Yu
Summary: The study shows that synchronized optimization of green and grey infrastructures can reduce costs and enhance the effectiveness of reducing runoff/pollutants. In the synchronous optimized scenarios, green infrastructures and grey infrastructures play different roles, contributing together to urban water resources management.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Thermodynamics
Zhiqiang Liu, Yanping Cui, Jiaqiang Wang, Chang Yue, Yawovi Souley Agbodjan, Yu Yang
Summary: This study explores an optimization model for properly sizing a multi-energy complementary integrated energy system (MCIES) considering uncertainties and achieving the best economic, environmental, and thermal comfort benefits. The non-dominated sorting genetic algorithm-II (NSGA-II) combined with TOPSIS and Shannon entropy method is used for optimization. Case studies demonstrate the effectiveness of the proposed approach.
Article
Computer Science, Interdisciplinary Applications
Saeed Gholizadeh, Fayegh Fattahi
Summary: This study utilizes an efficient algorithm for multi-objective performance-based seismic optimization of steel moment frames. Through the design and evaluation of multi-story steel frames, the effectiveness of the algorithm is demonstrated in achieving optimal designs with improved seismic performance and collapse capacity.
ENGINEERING WITH COMPUTERS
(2021)
Article
Computer Science, Interdisciplinary Applications
Alexandre Mathern, Olof Skogby Steinholtz, Anders Sjoberg, Magnus onnheim, Kristine Ek, Rasmus Rempling, Emil Gustavsson, Mats Jirstrand
Summary: The planning and design of buildings and civil engineering concrete structures involve complex problems with constraints, and the use of multi-objective optimization methods can provide more relevant design strategies. The potential of these methods remains unexploited in structural concrete design practice, but Bayesian optimization has shown promise in addressing constrained multi-objective optimization problems in structural design.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Automation & Control Systems
Guosen Li, Ting Zhou
Summary: This paper proposes a particle swarm optimizer based on reference point, termed RPPSO, which effectively handles global and local solutions in multimodal multi-objective optimization problems, achieving competitive performance on multiple benchmark test functions.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Mechanics
Xiang Peng, Yuliang Guo, Jiquan Li, Huaping Wu, Shaofei Jiang
Summary: This paper presents a multi-objective uncertainty optimization design methodology for hybrid composite structures considering multiple-scale uncertainties. The methodology involves uncertainty propagation analysis, quantification of macro material uncertainties using a neural network model, and the development of a multiple objective robust optimization design function. An adaptive nondominated sorting genetic algorithm II (NSGA-II) method is proposed to optimize the stacking sequence and material patches simultaneously. Engineering examples demonstrate that the proposed methodology can improve vibration characteristics while maintaining low material cost.
COMPOSITE STRUCTURES
(2022)