资源类型

期刊论文 2021

年份

2024 3

2023 160

2022 192

2021 156

2020 161

2019 154

2018 133

2017 126

2016 91

2015 104

2014 75

2013 61

2012 62

2011 52

2010 64

2009 57

2008 68

2007 82

2006 51

2005 41

展开 ︾

关键词

优化 18

遗传算法 13

多目标优化 9

优化设计 7

机器学习 7

神经网络 7

预测 6

可持续发展 5

可视化仿真 4

目标识别 4

稳健设计 4

BP神经网络 3

COVID-19 3

算法 3

CAN总线 2

Cu(In 2

GIS 2

GPS 2

HY-2 2

展开 ︾

检索范围：

排序： 展示方式：

Ahybrid biogeography-based optimization method for the inverse kinematics problem of an 8-DOF redundant

Zi-wu REN,Zhen-hua WANG,Li-ning SUN

《信息与电子工程前沿（英文）》 2015年 第16卷 第7期   页码 607-616 doi: 10.1631/FITEE.14a0335

摘要： The redundant humanoid manipulator has characteristics of multiple degrees of freedom and complex joint structure, and it is not easy to obtain its inverse kinematics solution. The inverse kinematics problem of a humanoid manipulator can be formulated as an equivalent minimization problem, and thus it can be solved using some numerical optimization methods. Biogeography-based optimization (BBO) is a new biogeography inspired optimization algorithm, and it can be adopted to solve the inverse kinematics problem of a humanoid manipulator. The standard BBO algorithm that uses traditional migration and mutation operators suffers from slow convergence and prematurity. A hybrid biogeography-based optimization (HBBO) algorithm, which is based on BBO and differential evolution (DE), is presented. In this hybrid algorithm, new habitats in the ecosystem are produced through a hybrid migration operator, that is, the BBO migration strategy and DE/best/1/bin differential strategy, to alleviate slow convergence at the later evolution stage of the algorithm. In addition, a Gaussian mutation operator is adopted to enhance the exploration ability and improve the diversity of the population. Based on these, an 8-DOF (degree of freedom) redundant humanoid manipulator is employed as an example. The end-effector error (position and orientation) and the ‘away limitation level’ value of the 8-DOF humanoid manipulator constitute the fitness function of HBBO. The proposed HBBO algorithm has been used to solve the inverse kinematics problem of the 8-DOF redundant humanoid manipulator. Numerical simulation results demonstrate the effectiveness of this method.

关键词： Inverse kinematics problem     8-DOF humanoid manipulator     Biogeography-based optimization (BBO)     Differential evolution (DE)    

HTML PDF 收藏

Reliability-based robust design optimization of vehicle components, Part I: Theory

Yimin ZHANG

《机械工程前沿（英文）》 2015年 第10卷 第2期   页码 138-144 doi: 10.1007/s11465-015-0333-2

摘要：

The reliability-based design optimization, the reliability sensitivity analysis and robust design method are employed to present a practical and effective approach for reliability-based robust design optimization of vehicle components. A procedure for reliability-based robust design optimization of vehicle components is proposed. Application of the method is illustrated by reliability-based robust design optimization of axle and spring. Numerical results have shown that the proposed method can be trusted to perform reliability-based robust design optimization of vehicle components.

关键词： vehicle components     reliability-based design optimization     reliability-based sensitivity analysis     multi-objective optimization     robust design    

HTML PDF 收藏

The source and transport of bioaerosols in the air: A review

《环境科学与工程前沿（英文）》 2021年 第15卷 第3期 doi: 10.1007/s11783-020-1336-8

摘要：

• Emission of microbe from local environments is a main source of bioaerosols.

关键词： Bioaerosols     Diffusion     Source identification     Biogeography    

HTML PDF 收藏

Reliability-based robust design optimization of vehicle components, Part II: Case studies

Yimin ZHANG

《机械工程前沿（英文）》 2015年 第10卷 第2期   页码 145-153 doi: 10.1007/s11465-015-0334-1

摘要：

The reliability-based optimization, the reliability-based sensitivity analysis and robust design method are employed to propose an effective approach for reliability-based robust design optimization of vehicle components in Part I. Applications of the method are further discussed for reliability-based robust optimization of vehicle components in this paper. Examples of axles,torsion bar, coil and composite springs are illustrated for numerical investigations. Results have shown the proposed method is an efficient method for reliability-based robust design optimization of vehicle components.

关键词： vehicle axles and springs     reliability-based design optimization     reliability-based sensitivity analysis     multi-objective optimization     robust design    

HTML PDF 收藏

Optimization of multi-objective integrated process planning and scheduling problem using a priority basedoptimization algorithm

Muhammad Farhan AUSAF,Liang GAO,Xinyu LI

《机械工程前沿（英文）》 2015年 第10卷 第4期   页码 392-404 doi: 10.1007/s11465-015-0353-y

摘要：

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

关键词： integrated process planning and scheduling (IPPS)     dispatching rules     priority based optimization algorithm     multi-objective optimization    

HTML PDF 收藏

Massively efficient filter for topology optimization based on the splitting of tensor product structure

《机械工程前沿（英文）》 2022年 第17卷 第4期 doi: 10.1007/s11465-022-0710-6

摘要： In this work, we put forward a massively efficient filter for topology optimization (TO) utilizing the splitting of tensor product structure. With the aid of splitting technique, the traditional weight matrices of B-splines and non-uniform rational B-spline implicit filters are decomposed equivalently into two or three submatrices, by which the sensitivity analysis is reformulated for the nodal design variables without altering the optimization process. Afterwards, an explicit sensitivity filter, which is decomposed by the splitting pipeline as that applied to implicit filter, is established in terms of the tensor product of the axial distances between adjacent element centroids, and the corresponding sensitivity analysis is derived for elemental design variables. According to the numerical results, the average updating time for the design variables is accelerated by two-order-of-magnitude for the decomposed filter compared with the traditional filter. In addition, the memory burden and computing time of the weight matrix are decreased by six- and three-order-of-magnitude for the decomposed filter. Therefore, the proposed filter is massively improved by the splitting of tensor product structure and delivers a much more efficient way of solving TO problems in the frameworks of isogeometric analysis and finite element analysis.

关键词： topology optimization     isogeometric analysis     finite element analysis     tensor product structure     sensitivity analysis    

HTML PDF 收藏

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

《结构与土木工程前沿（英文）》 2023年 第17卷 第1期   页码 25-36 doi: 10.1007/s11709-022-0908-z

摘要： In recent years, tunnel boring machines (TBMs) have been widely used in tunnel construction. However, the TBM control parameters set based on operator experience may not necessarily be suitable for certain geological conditions. Hence, a method to optimize TBM control parameters using an improved loss function-based artificial neural network (ILF-ANN) combined with quantum particle swarm optimization (QPSO) is proposed herein. The purpose of this method is to improve the TBM performance by optimizing the penetration and cutterhead rotation speeds. Inspired by the regularization technique, a custom artificial neural network (ANN) loss function based on the penetration rate and rock-breaking specific energy as TBM performance indicators is developed in the form of a penalty function to adjust the output of the network. In addition, to overcome the disadvantage of classical error backpropagation ANNs, i.e., the ease of falling into a local optimum, QPSO is adopted to train the ANN hyperparameters (weight and bias). Rock mass classes and tunneling parameters obtained in real time are used as the input of the QPSO-ILF-ANN, whereas the cutterhead rotation speed and penetration are specified as the output. The proposed method is validated using construction data from the Songhua River water conveyance tunnel project. Results show that, compared with the TBM operator and QPSO-ANN, the QPSO-ILF-ANN effectively increases the TBM penetration rate by 14.85% and 13.71%, respectively, and reduces the rock-breaking specific energy by 9.41% and 9.18%, respectively.

关键词： tunnel boring machine     control parameter optimization     quantum particle swarm optimization     artificial neural network     tunneling energy efficiency    

HTML PDF 收藏

Synergistic optimization framework for the process synthesis and design of biorefineries

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 251-273 doi: 10.1007/s11705-021-2071-9

摘要： The conceptual process design of novel bioprocesses in biorefinery setups is an important task, which remains yet challenging due to several limitations. We propose a novel framework incorporating superstructure optimization and simulation-based optimization synergistically. In this context, several approaches for superstructure optimization based on different surrogate models can be deployed. By means of a case study, the framework is introduced and validated, and the different superstructure optimization approaches are benchmarked. The results indicate that even though surrogate-based optimization approaches alleviate the underlying computational issues, there remains a potential issue regarding their validation. The development of appropriate surrogate models, comprising the selection of surrogate type, sampling type, and size for training and cross-validation sets, are essential factors. Regarding this aspect, satisfactory validation metrics do not ensure a successful outcome from its embedded use in an optimization problem. Furthermore, the framework’s synergistic effects by sequentially performing superstructure optimization to determine candidate process topologies and simulation-based optimization to consolidate the process design under uncertainty offer an alternative and promising approach. These findings invite for a critical assessment of surrogate-based optimization approaches and point out the necessity of benchmarking to ensure consistency and quality of optimized solutions.

关键词： biotechnology     surrogate modelling     superstructure optimization     simulation-based optimization     process design    

HTML PDF 收藏

Analysis of energy saving optimization of campus buildings based on energy simulation

Dingding TONG, Jing ZHAO

《能源前沿（英文）》 2013年 第7卷 第3期   页码 388-398 doi: 10.1007/s11708-013-0273-7

摘要： The energy consumption of campus buildings has specific characteristics, because of the concentrated distribution of people’s working time and locations that change in line with distinct seasonal features. The traditional energy system design and operation for campus buildings is only based on the constant room temperature, such as 25°C in summer and 18°C in winter in China, not taking into consideration the real heating or cooling load characteristics of campus buildings with different functions during the whole day and whole year, which usually results in a lot of energy waste. This paper proposes to set different set-point temperatures in different operation stages of public and residential campus buildings to reduce the heating and cooling design load for energy station and total campus energy consumption for annual operation. Taking a campus under construction in Tianjin, China as an example, two kinds of single building models were established as the typical public building and residential building models on the campus. Besides, the models were simulated at both set-point room temperature and constant room temperature respectively. The comparison of the simulation results showed that the single building energy saving method of the peak load clipping could be used for further analysis of the annual energy consumption of campus building groups. The results proved that the strategy of set-point temperature optimization could efficiently reduce the design load and energy consumption of campus building groups.

关键词： campus buildings     set-point temperature     energy simulation     energy saving optimization    

HTML PDF 收藏

Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

《机械工程前沿（英文）》 2021年 第16卷 第2期   页码 393-409 doi: 10.1007/s11465-020-0613-3

摘要： As an important part of product design and manufacturing, assembly sequence planning (ASP) has a considerable impact on product quality and manufacturing costs. ASP is a typical NP-complete problem that requires effective methods to find the optimal or near-optimal assembly sequence. First, multiple assembly constraints and rules are incorporated into an assembly model. The assembly constraints and rules guarantee to obtain a reasonable assembly sequence. Second, an algorithm called SOS-ACO that combines symbiotic organisms search (SOS) and ant colony optimization (ACO) is proposed to calculate the optimal or near-optimal assembly sequence. Several of the ACO parameter values are given, and the remaining ones are adaptively optimized by SOS. Thus, the complexity of ACO parameter assignment is greatly reduced. Compared with the ACO algorithm, the hybrid SOS-ACO algorithm finds optimal or near-optimal assembly sequences in fewer iterations. SOS-ACO is also robust in identifying the best assembly sequence in nearly every experiment. Lastly, the performance of SOS-ACO when the given ACO parameters are changed is analyzed through experiments. Experimental results reveal that SOS-ACO has good adaptive capability to various values of given parameters and can achieve competitive solutions.

关键词： assembly sequence planning     ant colony optimization     symbiotic organisms search     parameter optimization    

HTML PDF 收藏

Distributionally robust optimization of home energy management system based on receding horizon optimization

Jidong WANG, Boyu CHEN, Peng LI, Yanbo CHE

《能源前沿（英文）》 2020年 第14卷 第2期   页码 254-266 doi: 10.1007/s11708-020-0665-4

摘要： This paper investigates the scheduling strategy of schedulable load in home energy management system (HEMS) under uncertain environment by proposing a distributionally robust optimization (DRO) method based on receding horizon optimization (RHO-DRO). First, the optimization model of HEMS, which contains uncertain variable outdoor temperature and hot water demand, is established and the scheduling problem is developed into a mixed integer linear programming (MILP) by using the DRO method based on the ambiguity sets of the probability distribution of uncertain variables. Combined with RHO, the MILP is solved in a rolling fashion using the latest update data related to uncertain variables. The simulation results demonstrate that the scheduling results are robust under uncertain environment while satisfying all operating constraints with little violation of user thermal comfort. Furthermore, compared with the robust optimization (RO) method, the RHO-DRO method proposed in this paper has a lower conservation and can save more electricity for users.

关键词： distributionally robust optimization (DRO)     home energy management system (HEMS)     receding horizon optimization (RHO)     uncertainties    

HTML PDF 收藏

Level set band method: A combination of density-based and level set methods for the topology optimization

Peng WEI, Wenwen WANG, Yang YANG, Michael Yu WANG

《机械工程前沿（英文）》 2020年 第15卷 第3期   页码 390-405 doi: 10.1007/s11465-020-0588-0

摘要： The level set method (LSM), which is transplanted from the computer graphics field, has been successfully introduced into the structural topology optimization field for about two decades, but it still has not been widely applied to practical engineering problems as density-based methods do. One of the reasons is that it acts as a boundary evolution algorithm, which is not as flexible as density-based methods at controlling topology changes. In this study, a level set band method is proposed to overcome this drawback in handling topology changes in the level set framework. This scheme is proposed to improve the continuity of objective and constraint functions by incorporating one parameter, namely, level set band, to seamlessly combine LSM and density-based method to utilize their advantages. The proposed method demonstrates a flexible topology change by applying a certain size of the level set band and can converge to a clear boundary representation methodology. The method is easy to implement for improving existing LSMs and does not require the introduction of penalization or filtering factors that are prone to numerical issues. Several 2D and 3D numerical examples of compliance minimization problems are studied to illustrate the effects of the proposed method.

关键词： level set method     topology optimization     density-based method     level set band    

HTML PDF 收藏

Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

《机械工程前沿（英文）》 2021年 第16卷 第1期   页码 80-96 doi: 10.1007/s11465-020-0614-2

摘要： Topology optimization is a pioneer design method that can provide various candidates with high mechanical properties. However, high resolution is desired for optimum structures, but it normally leads to a computationally intractable puzzle, especially for the solid isotropic material with penalization (SIMP) method. In this study, an efficient, high-resolution topology optimization method is developed based on the super-resolution convolutional neural network (SRCNN) technique in the framework of SIMP. SRCNN involves four processes, namely, refinement, path extraction and representation, nonlinear mapping, and image reconstruction. High computational efficiency is achieved with a pooling strategy that can balance the number of finite element analyses and the output mesh in the optimization process. A combined treatment method that uses 2D SRCNN is built as another speed-up strategy to reduce the high computational cost and memory requirements for 3D topology optimization problems. Typical examples show that the high-resolution topology optimization method using SRCNN demonstrates excellent applicability and high efficiency when used for 2D and 3D problems with arbitrary boundary conditions, any design domain shape, and varied load.

关键词： topology optimization     convolutional neural network     high resolution     density-based    

HTML PDF 收藏

Distinct community assembly processes underlie significant spatiotemporal dynamics of abundant and rare bacterioplankton in the Yangtze River

《环境科学与工程前沿（英文）》 2022年 第16卷 第6期 doi: 10.1007/s11783-021-1513-4

摘要：

• Season and landform influenced spatiotemporal patterns of abundant and rare taxa.

关键词： Rare taxa     Biogeography     Community assembly     Bacterioplankton     The Yangtze River    

HTML PDF 收藏

Multi-objective optimization for the multi-mode finance-based project scheduling problem

Sameh Al-SHIHABI, Mohammad AlDURGAM

《工程管理前沿（英文）》 2020年 第7卷 第2期   页码 223-237 doi: 10.1007/s42524-020-0097-1

摘要： The finance-based scheduling problem (FBSP) is about scheduling project activities without exceeding a credit line financing limit. The FBSP is extended to consider different execution modes that result in the multi-mode FBSP (MMFBSP). Unfortunately, researchers have abandoned the development of exact models to solve the FBSP and its extensions. Instead, researchers have heavily relied on the use of heuristics and meta-heuristics, which do not guarantee solution optimality. No exact models are available for contractors who look for optimal solutions to the multi-objective MMFBSP. CPLEX, which is an exact solver, has witnessed a significant decrease in its computation time. Moreover, its current version, CPLEX 12.9, solves multi-objective optimization problems. This study presents a mixed-integer linear programming model for the multi-objective MMFBSP. Using CPLEX 12.9, we discuss several techniques that researchers can use to optimize a multi-objective MMFBSP. We test our model by solving several problems from the literature. We also show how to solve multi-objective optimization problems by using CPLEX 12.9 and how computation time increases as problem size increases. The small increase in computation time compared with possible cost savings make exact models a must for practitioners. Moreover, the linear programming-relaxation of the model, which takes seconds, can provide an excellent lower bound.

关键词： multi-objective optimization     finance-based scheduling     multi-mode project scheduling     mixed-integer linear programming     CPLEX    

HTML PDF 收藏

标题 作者 时间 类型 操作

Ahybrid biogeography-based optimization method for the inverse kinematics problem of an 8-DOF redundant

Zi-wu REN,Zhen-hua WANG,Li-ning SUN

期刊论文

Reliability-based robust design optimization of vehicle components, Part I: Theory

Yimin ZHANG

期刊论文

The source and transport of bioaerosols in the air: A review

期刊论文

Reliability-based robust design optimization of vehicle components, Part II: Case studies

Yimin ZHANG

期刊论文

Optimization of multi-objective integrated process planning and scheduling problem using a priority basedoptimization algorithm

Muhammad Farhan AUSAF,Liang GAO,Xinyu LI

期刊论文

Massively efficient filter for topology optimization based on the splitting of tensor product structure

期刊论文

QPSO-ILF-ANN-based optimization of TBM control parameters considering tunneling energy efficiency

期刊论文

Synergistic optimization framework for the process synthesis and design of biorefineries

期刊论文

Analysis of energy saving optimization of campus buildings based on energy simulation

Dingding TONG, Jing ZHAO

期刊论文

Ant colony optimization for assembly sequence planning based on parameters optimization

Zunpu HAN, Yong WANG, De TIAN

期刊论文

Distributionally robust optimization of home energy management system based on receding horizon optimization

Jidong WANG, Boyu CHEN, Peng LI, Yanbo CHE

期刊论文

Level set band method: A combination of density-based and level set methods for the topology optimization

Peng WEI, Wenwen WANG, Yang YANG, Michael Yu WANG

期刊论文

Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

期刊论文

Distinct community assembly processes underlie significant spatiotemporal dynamics of abundant and rare bacterioplankton in the Yangtze River

期刊论文

Multi-objective optimization for the multi-mode finance-based project scheduling problem

Sameh Al-SHIHABI, Mohammad AlDURGAM

期刊论文