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Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

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ENGINEERING OPTIMIZATION 2017年第7期49卷 1211-1225页

作者： Ouyang, Huei-Tau Natl Ilan Univ Dept Civil Engn Yilan Taiwan

Three types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive model with exogenous inputs (LARX), the nonlinear autoregressive model with exogenous inputs with wavelet function (NLARX-W) and the nonlinear autoregressive model with exogenous inputs with sigmoid function (NLARX-S). The forecast performance was evaluated by three indices: coefficient of efficiency, error in peak water level and relative time shift. Historical typhoon data were used to establish water-level forecasting models that satisfy all three objectives. A multi-objective genetic algorithm was employed to search for the Pareto-optimal model set that satisfies all three objectives and select the ideal models for the three indices. Findings showed that the optimized nonlinear models (NLARX-W and NLARX-S) outperformed the linear model (LARX). Among the nonlinear models, the optimized NLARX-W model achieved a more balanced performance on the three indices than the NLARX-S models and is recommended for inundation forecasting during typhoons.

关键词： Inundation typhoon ARX multi-objective genetic algorithm Pareto-optimal set

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Optimization investigation on configuration parameters of spiral-wound heat exchanger using genetic Aggregation response surface and multi-objective genetic algorithm

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APPLIED THERMAL ENGINEERING 2017年 119卷 603-609页

作者： Wang, Simin Jian, Guanping Xiao, Juan Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Shanxi Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

Based on the method combining genetic Aggregation response surface and multi-objective genetic algorithm, the effects of configuration parameters of spiral-wound heat exchanger (SWHE) on flow and heat transfer characteristics were numerically studied. The results show that the shell-side pressure drop of the spiral-wound heat exchanger decreases with the increase of layer pitch, winding angle and tube pitch, respectively. The shell-side heat transfer coefficient of the spiral-wound heat exchanger decreases with the increase of layer pitch and increases with the external diameter of tube. The shell-side heat transfer coefficient increases firstly with the increase of the winding angle and then decreases. The sensitivity analysis also shows that the shell-side flow and heat transfer characteristics are mainly affected by the winding angle. Under the working condition, the pressure drop and heat transfer coefficient are both negatively correlated with the layer pitch. And the winding angle is negatively correlated with the pressure drop, but positively correlated with the heat transfer coefficient. Three optimal configurations were obtained by the multi-Object genetic algorithm based on genetic Aggregation response surface. Compared with the original configuration, the average heat transfer coefficient of improved ones is enhanced by 2.93%, while the average pressure drop is reduced by 40.27%. The results are of great significance for the design of spiral-wound heat exchanger. (C) 2017 Published by Elsevier Ltd.

关键词： Spiral-wound heat exchanger Structural parameters genetic Aggregation multi-objective genetic algorithm

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CFD modeling and optimization of a latent heat storage unit for running a solar assisted single effect Li-Br absorption chiller using multi-objective genetic algorithm

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SUSTAINABLE CITIES AND SOCIETY 2017年 34卷 321-334页

作者： Ghorbani, Babak Kowsary, Farshad Ebrahimi, Sasan Vijayaraghavan, Krishna Simon Fraser Univ Sch Mechatron Syst Engn 250-13450 102 Ave Surrey BC V3T 0A3 Canada Univ Tehran Mech Engn Dept Tehran Iran

In this paper, the feasibility of a solar absorption refrigeration system to be powered by a latent heat storage (LHS) unit is investigated for a representative building. A single effect absorption chiller, utilizing Li-Br and water as working fluids is thermodynamically simulated. Then, the simulation of the latent heat storage unit is performed by applying finite difference method and the results were validated by the researches in the literature. Then, the geometry of a phase change material (PCM) based LHS system was optimized using multi-objective genetic algorithm for simultaneously minimizing the charging time, and maximizing the discharging time. Since the paper considers conflicting objectives, a Pareto front is presented that can be used for obtaining the optimum geometry according to the environmental conditions and working hours of the absorption system. As an illustrative example, the designed heat storage system was shown to be able to drive the 72 kW generator of an absorption system, for at least 10 h of operation in the discharging mode with the absence of sunlight. Therefore, it is possible to run absorption chillers under low-load operation conditions using the solar energy if the appropriate storage unit, such as what is introduced here, is used.

关键词： Single effect absorption system Li-Br and water Latent heat storage multi-objective genetic algorithm Optimization

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Configuration optimization of shell-and-tube heat exchangers with helical baffles using multi-objective genetic algorithm based on fluid-structure interaction

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2017年 85卷 62-69页

作者： Wang, Simin Xiao, Juan Wang, Jiarui Jian, Guanping Wen, Jian Zhang, Zaoxiao Xi An Jiao Tong Univ Sch Chem Engn & Technol Xian 710049 Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Xian 710049 Peoples R China

The configuration parameters of helical angle and overlapped degree of shell-and-tube heat exchangers with helical baffles have been discussed for the thermal-structural comprehensive performance. Based on fluid structure interaction theory, a method on configuration optimization of shell-and-tube heat exchangers with helical baffles is introduced using second-order polynomial regression response surface combined with multi objective genetic algorithm. The results show that the heat transfer coefficient per unit pressure drop of shell and -tube heat exchangers with helical baffles increases firstly and then decreases with the increase of helical angle, and decreases with the increase of overlapped degree under certain shell-inlet velocity. And the performance of flow and heat transfer is more sensitive to helical angle compared with overlapped degree. The maximum shear stress increases with helical angle, but it is almost unaffected by overlapped degree for mechanical properties of helical baffles. The objectives of optimization are the heat transfer coefficient per unit pressure drop maximizing and maximum shear stress minimizing with scope of allowable stress, and three optimal structures are obtained. The optimal results indicate that the heat transfer coefficient per unit pressure drop increases averagely by 14.1%, the maximum shear stress decreases averagely by 4.1%, which provides theoretical guidance for industrial design of shell-and-tube heat exchangers with helical baffles.

关键词： Shell-and-tube heat exchangers with helical baffles Fluid-structure interaction multi-objective genetic algorithm Configuration optimization Mechanical properties

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Dynamic configuration of QC allocating problem based on multi-objective genetic algorithm

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JOURNAL OF INTELLIGENT MANUFACTURING 2017年第3期28卷 847-855页

作者： Liang, ChengJi Li, MiaoMiao Lu, Bo Gu, Tianyi Jo, Jungbok Ding, Yi Shanghai Maritime Univ Logist Res Ctr Shanghai Peoples R China Dalian Univ Inst E Commerce & Modern Logist Dalian Peoples R China UCAS Sch Management Beijing Peoples R China Shanghai Int Port Grp Co Ltd Shanghai Peoples R China Dongseo Univ Div Comp & Informat Engn Busan South Korea

Solving the problem of allocating and scheduling quay cranes (QCs) is very important to ensure favorable port service. This work proposes a bi-criteria mixed integer programming model of the continual and dynamic arrival of several vessels at a port. A multi-objective genetic algorithm is applied to solve the problem in three cases. The results thus obtained confirm the feasibility and effectiveness of the model and GA. Additionally, the multi-objective solution considering both the total duration for which vessels stay in the port and QCs move is the best, as determined by comparing with considering only the total time for which vessels stay in the port or QCs move, as it considers, and it balances these two objectives.

关键词： Port facilities multi-objective genetic algorithm Quay crane scheduling Pareto optimal solution

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A Novel Linear Time Invariant Systems Order Reduction Approach Based on a Cooperative multi-objective genetic algorithm 8th

A Novel Linear Time Invariant Systems Order Reduction Approa...

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8th International Conference on Swarm Intelligence (ICSI)

作者： Ryzhikov, Ivan Brester, Christina Semenkin, Eugene Siberian State Aerosp Univ Krasnoyarsk Russia

ISBN: (纸本)9783319618333;9783319618326

Cooperative multi-objective optimization tool is proposed for solving the order reduction problem for linear time invariant systems. Normally, the adequacy of an order reduction problem solution is estimated using two different criteria, but only one of them identifies the model. In this study, it was suggested to identify the parameters using both of the criteria, and since the criteria are complex and multi-extremum there is a need for a powerful optimization algorithm to be used. The proposed approach is based on the cooperation of heterogeneous algorithms implemented in the islands scheme and it has proved its efficiency in solving various multi-objective optimization problems. It allows us to receive a set of lower order models, which are non-dominated solutions for the given criteria and an estimation of the Pareto set. The results of this study are compared to the results of solving the same problems using various approaches and heuristic optimization tools and it is demonstrated that the set of solutions not only outperforms these approaches by the main criterion, but also provides good solutions with another criterion and a combination of them using the same computational resources.

关键词： Cooperation meta-heuristics multi-objective optimization multi-objective genetic algorithm Linear time invariant system Parameters identification

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Traffic accident severity prediction using a novel multi-objective genetic algorithm

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INTERNATIONAL JOURNAL OF CRASHWORTHINESS 2017年第4期22卷 425-440页

作者： Hashmienejad, Seyed Hessam-Allah Hasheminejad, Seyed Mohammad Hossein Razi Univ Dept Civil Engn Kermanshah Iran Alzahra Univ Dept Comp Engn Tehran Iran

Prediction of traffic accident severity is a motor vehicle traffic challenge due to its impact on saving human lives. There are several researches in the literature to predict traffic accident severity based on artificial neural networks (ANNs), support vector machines (SVMs), decision trees (DTs) and other classification methods. In fact, the main disadvantage of ANNs and SVMs is lack of interpretation for human and the main disadvantage of classical DTs such as C4.5, ID3 and CART is their low accuracy. To address these drawbacks, in this paper we propose a novel rule-based method to predict traffic accident severity according to user's preferences instead of conventional DTs. In the proposed method, we customised a multi-objective genetic algorithm, i.e. Non-Dominated Sorting genetic algorithm (NSGA-II), to optimise and identify rules according to Support, Confidence and Comprehensibility metrics. The goal of the proposed method is providing facilities to make use of the knowledge of users, including traffic police, roads and transportation engineers and trade-off among all the conflicting objectives. The proposed method is evaluated by a traffic accident data set including 14211 accidents in rural and urban roads in Tehran Province of Iran for a period of 5years (2008-2013). The evaluation results revealed that the proposed method outperforms the classification methods such as ANN, SVM, and conventional DTs according to classification metrics like accuracy (88.2%), and performance metrics of rules like support and confidence (0.79 and 0.74, respectively).

关键词： Traffic accident severity prediction multi-objective genetic algorithm decision trees Non-Dominated Sorting genetic algorithm

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Statistical modeling and optimization of resistance spot welding process parameters using neural networks and multi-objective genetic algorithm

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JOURNAL OF INTELLIGENT MANUFACTURING 2016年第3期27卷 549-559页

作者： Pashazadeh, Hamed Gheisari, Yousof Hamedi, Mohsen Islamic Azad Univ East Azarbaijan Sci & Res Branch Young Researchers & Elites Club Tabriz Iran Islamic Azad Univ Bushehr Branch Dept Math Bushehr Iran Univ Tehran Sch Mech Engn Coll Engn Tehran Iran

Resistance spot welding (RSW) is a highly used joining procedure in automotive industry. In RSW, after a number of welds the welding electrode starts to wear and its diameter changes. This causes the weld nugget diameter abnormal variations and consequently reduces the weld strength. Therefore the tip of the electrode should be dressed in RSW. Selecting the optimum time for the welding electrode tip dressing operations is very important. In this research three welding parameters including the welding time, the welding current, and the welding pressure were identified as the main effective parameters on the weld nugget dimensions including the weld nugget diameter and height using full factorial design of experiments. Then using hybrid combination of the artificial neural networks and multi-objective genetic algorithm, the optimized values of the aforementioned parameters were specified. Finally experiments were fulfilled to estimate the admissible number of the weld spots which should be done before the electrode tip dressing operation.

关键词： Resistance spot welding Electrode tip dressing Design of experiments Artificial neural networks multi-objective genetic algorithm

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Finding Robust Adaptation Gene Regulatory Networks Using multi-objective genetic algorithm

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2016年第3期13卷 571-577页

作者： Ren, Hai-Peng Huang, Xiao-Na Hao, Jia-Xuan Xian Univ Technol Dept Informat & Control Engn Xian 710048 Peoples R China Shaanxi Key Lab Complex Syst Control & Intelligen Xian Peoples R China HeXi Univ Sch Phys & Electromech Engn Zhangye 734000 Gansu Peoples R China

Robust adaptation plays a key role in gene regulatory networks, and it is thought to be an important attribute for the organic or cells to survive in fluctuating conditions. In this paper, a simplified three-node enzyme network is modeled by the Michaelis-Menten rate equations for all possible topologies, and a family of topologies and the corresponding parameter sets of the network with satisfactory adaptation are obtained using the multi-objective genetic algorithm. The proposed approach improves the computation efficiency significantly as compared to the time consuming exhaustive searching method. This approach provides a systemic way for searching the feasible topologies and the corresponding parameter sets to make the gene regulatory networks have robust adaptation. The proposed methodology, owing to its universality and simplicity, can be used to address more complex issues in biological networks.

关键词： Gene regulatory networks Michaelis-Menten rate equations robust adaptation multi-objective genetic algorithm Pareto ranking

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Application of camera calibrating model to space manipulator with multi-objective genetic algorithm

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Journal of Central South University 2016年第8期23卷 1937-1943页

作者：王中宇江文松王岩庆 Key Laboratory of Precision Opto-Mechatronics Technology of Ministry of Education (Beihang University) Beijing 100191 China Academy of Opto-Electronics Chinese Academy of Sciences Beijing 100094 China

The multi-objective genetic algorithm(MOGA) is proposed to calibrate the non-linear camera model of a space manipulator to improve its locational accuracy. This algorithm can optimize the camera model by dynamic balancing its model weight and multi-parametric distributions to the required accuracy. A novel measuring instrument of space manipulator is designed to orbital simulative motion and locational accuracy test. The camera system of space manipulator, calibrated by MOGA algorithm, is used to locational accuracy test in this measuring instrument. The experimental result shows that the absolute errors are [0.07, 1.75] mm for MOGA calibrating model, [2.88, 5.95] mm for MN method, and [1.19, 4.83] mm for LM method. Besides, the composite errors both of LM method and MN method are approximately seven times higher that of MOGA calibrating model. It is suggested that the MOGA calibrating model is superior both to LM method and MN method.

关键词： space manipulator camera calibration multi-objective genetic algorithm orbital simulation and measurement

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