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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    

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Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

《工程管理前沿（英文）》 2020年 第7卷 第3期   页码 335-358 doi: 10.1007/s42524-020-0112-6

摘要： System reliability optimization problems have been widely discussed to maximize system reliability with resource constraints. Birnbaum importance is a well-known method for evaluating the effect of component reliability on system reliability. Many importance measures (IMs) are extended for binary, multistate, and continuous systems from different aspects based on the Birnbaum importance. Recently, these IMs have been applied in allocating limited resources to the component to maximize system performance. Therefore, the significance of Birnbaum importance is illustrated from the perspective of probability principle and gradient geometrical sense. Furthermore, the equations of various extended IMs are provided subsequently. The rules for simple optimization problems are summarized to enhance system reliability by using ranking or heuristic methods based on IMs. The importance-based optimization algorithms for complex or large-scale systems are generalized to obtain remarkable solutions by using IM-based local search or simplification methods. Furthermore, a general framework driven by IM is developed to solve optimization problems. Finally, some challenges in system reliability optimization that need to be solved in the future are presented.

关键词： importance measure     system performance     reliability optimization     optimization rules     optimization algorithms    

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Split-order consolidation optimization for online supermarkets: Process analysis and optimization models

《工程管理前沿（英文）》   页码 499-516 doi: 10.1007/s42524-022-0221-5

摘要： The large-scale online supermarket is a newly emerging online retailing mode which brings great convenience to people. Online supermarkets are characterized by having large amounts of daily orders with potentially multiple items, diverse delivery times, and a high order-split rate. Multiple shipments for one order caused by order splitting result in high cost and disturbance and a large number of discarded consumable packages at online retailers and customers, causing severe damage to the environment. Accordingly, research on split-order consolidation fulfilment is critical for the advancement of the practice and theory in the context of highly complex online retailing. This paper first analyzes the characteristics and the challenges associated with the split-order consolidation problem that online supermarket is confronting and summarizes the new operational process of split-order consolidation fulfilment. Then, a time–space network optimization model is built, and its corresponding solution algorithm is presented to solve the questions of where and when to consolidate the split orders. Finally, the computation results of the numerical experiments are provided to verify the effectiveness of the algorithm, and a sensitivity analysis of the relevant parameters is performed. This work highlights the effect of order consolidation processes and fulfilment methods on the order fulfilment decision-making for online supermarkets. The purpose of this article is to help pave the way for more effective online supermarket management and order implementation.

关键词： online supermarkets     split-order consolidation     time–space network     genetic algorithm    

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Design and optimization of reactive distillation: a review

《化学科学与工程前沿（英文）》 2022年 第16卷 第6期   页码 799-818 doi: 10.1007/s11705-021-2128-9

摘要： Reactive distillation process, a representative process intensification technology, has been widely applied in the chemical industry. However, due to the strong interaction between reaction and separation, the extension of reactive distillation technology is restricted by the difficulties in process analysis and design. To overcome this problem, the design and optimization of reactive distillation have been widely studied and illustrated for plenty of reactive mixtures over the past three decades. These design and optimization methods of the reactive distillation process are classified into three categories: graphical, optimization-based, and evolutionary/heuristic methods. The primary objective of this article is to provide an up-to-date review of the existing design and optimization methods. Desired and output information, advantages and limitations of each method are stated, the modification and development for original methodologies are also reviewed. Perspectives on future research on the design and optimization of reactive distillation method are proposed for further research.

关键词： reactive distillation     process intensification     design method     reactive phase diagram     optimization algorithm    

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Review on the design and optimization of hydrogen liquefaction processes

Liang YIN, Yonglin JU

《能源前沿（英文）》 2020年 第14卷 第3期   页码 530-544 doi: 10.1007/s11708-019-0657-4

摘要： The key technologies of liquefied hydrogen have been developing rapidly due to its prospective energy exchange effectiveness, zero emissions, and long distance and economic transportation. However, hydrogen liquefaction is one of the most energy-intensive industrial processes. A small reduction in energy consumption and an improvement in efficiency may decrease the operating cost of the entire process. In this paper, the detailed progress of design and optimization for hydrogen liquefaction in recent years are summarized. Then, based on the refrigeration cycles, the hydrogen liquefaction processes are divided into two parts, namely precooled liquefaction process and cascade liquefaction process. Among the existing technologies, the SEC of most hydrogen liquefaction processes is limited in the range of 5–8 (LH : liquid hydrogen). The exergy efficiencies of processes are around 40% to 60%. Finally, several future improvements for hydrogen liquefaction process design and optimization are proposed. The mixed refrigerants (MRs) as the working fluids of the process and the combination of the traditional hydrogen liquefaction process with the renewable energy technology will be the great prospects for development in near future.

关键词： hydrogen liquefaction     energy consumption     efficiency     optimization    

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Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristic

《结构与土木工程前沿（英文）》 2022年 第16卷 第1期   页码 57-74 doi: 10.1007/s11709-021-0784-y

摘要： Steel dome structures, with their striking structural forms, take a place among the impressive and aesthetic load bearing systems featuring large internal spaces without internal columns. In this paper, the seismic design optimization of spatial steel dome structures is achieved through three recent metaheuristic algorithms that are water strider (WS), grey wolf (GW), and brain storm optimization (BSO). The structural elements of the domes are treated as design variables collected in member groups. The structural stress and stability limitations are enforced by ASD-AISC provisions. Also, the displacement restrictions are considered in design procedure. The metaheuristic algorithms are encoded in MATLAB interacting with SAP2000 for gathering structural reactions through open application programming interface (OAPI). The optimum spatial steel dome designs achieved by proposed WS, GW, and BSO algorithms are compared with respect to solution accuracy, convergence rates, and reliability, utilizing three real-size design examples for considering both the previously reported optimum design results obtained by classical metaheuristic algorithms and a gradient descent-based hyperband optimization (HBO) algorithm.

关键词： steel dome optimization     water strider algorithm     grey wolf algorithm     brain storm optimization algorithm     hyperband optimization algorithm    

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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    

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Footholds optimization for legged robots walking on complex terrain

《机械工程前沿（英文）》 2023年 第18卷 第2期 doi: 10.1007/s11465-022-0742-y

摘要： This paper proposes a novel continuous footholds optimization method for legged robots to expand their walking ability on complex terrains. The algorithm can efficiently run onboard and online by using terrain perception information to protect the robot against slipping or tripping on the edge of obstacles, and to improve its stability and safety when walking on complex terrain. By relying on the depth camera installed on the robot and obtaining the terrain heightmap, the algorithm converts the discrete grid heightmap into a continuous costmap. Then, it constructs an optimization function combined with the robot’s state information to select the next footholds and generate the motion trajectory to control the robot’s locomotion. Compared with most existing footholds selection algorithms that rely on discrete enumeration search, as far as we know, the proposed algorithm is the first to use a continuous optimization method. We successfully implemented the algorithm on a hexapod robot, and verified its feasibility in a walking experiment on a complex terrain.

关键词： footholds optimization     legged robot     complex terrain adapting     hexapod robot     locomotion control    

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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    

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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    

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Discussion on the System Optimization of the Energy Development Strategy and Plan

Da-di Zhou

《工程管理前沿（英文）》 2014年 第1卷 第2期   页码 147-152 doi: 10.15302/J-FEM-2014022

摘要： Energy is an important basis for economic and social development, and is a critical economic sector. Due to the complexity of the energy system, the interactive relationship with economic and social development, and the enormous investment involved, the optimization of the energy system is of great significance. We should make efforts to develop targets and specific approaches for the rational and optimal development of an energy system in order to avoid big losses due to systematic mistakes.

关键词： energy development strategy     planning system     system optimization    

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Robust isogeometric topology optimization for piezoelectric actuators with uniform manufacturability

《机械工程前沿（英文）》 2022年 第17卷 第2期 doi: 10.1007/s11465-022-0683-5

摘要： Piezoelectric actuators have received substantial attention among the industry and academia due to quick responses, such as high output force, high stiffness, high accuracy, and precision. However, the design of piezoelectric actuators always suffers from the emergence of several localized hinges with only one-node connection, which have difficulty satisfying manufacturing and machining requirements (from the over- or under-etching devices). The main purpose of the current paper is to propose a robust isogeometric topology optimization (RITO) method for the design of piezoelectric actuators, which can effectively remove the critical issue induced by one-node connected hinges and simultaneously maintain uniform manufacturability in the optimized topologies. In RITO, the isogeometric analysis replacing the conventional finite element method is applied to compute the unknown electro elastic fields in piezoelectric materials, which can improve numerical accuracy and then enhance iterative stability. The erode–dilate operator is introduced in topology representation to construct the eroded, intermediate, and dilated density distribution functions by non-uniform rational B-splines. Finally, the RITO formulation for the design of piezoelectric materials is developed, and several numerical examples are performed to test the effectiveness and efficiency of the proposed RITO method.

关键词： piezoelectric actuator     isogeometric topology optimization     uniform manufacturability     robust formulation     density distribution function    

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Data analytics and optimization for smart industry

Lixin TANG, Ying MENG

《工程管理前沿（英文）》 2021年 第8卷 第2期   页码 157-171 doi: 10.1007/s42524-020-0126-0

摘要： Industrial intelligence is a core technology in the upgrading of the production processes and management modes of traditional industries. Motivated by the major development strategies and needs of industrial intellectualization in China, this study presents an innovative fusion structure that encompasses the theoretical foundation and technological innovation of data analytics and optimization, as well as their application to smart industrial engineering. First, this study describes a general methodology for the fusion of data analytics and optimization. Then, it identifies some data analytics and system optimization technologies to handle key issues in smart manufacturing. Finally, it provides a four-level framework for smart industry based on the theoretical and technological research on the fusion of data analytics and optimization. The framework uses data analytics to perceive and analyze industrial production and logistics processes. It also demonstrates the intelligent capability of planning, scheduling, operation optimization, and optimal control. Data analytics and system optimization technologies are employed in the four-level framework to overcome some critical issues commonly faced by manufacturing, resources and materials, energy, and logistics systems, such as high energy consumption, high costs, low energy efficiency, low resource utilization, and serious environmental pollution. The fusion of data analytics and optimization allows enterprises to enhance the prediction and control of unknown areas and discover hidden knowledge to improve decision-making efficiency. Therefore, industrial intelligence has great importance in China’s industrial upgrading and transformation into a true industrial power.

关键词： data analytics     system optimization     smart industry    

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Structural optimization of typical rigid links in a parallel kinematic machine

Xinjun LIU, Zhidong LI, Xiang CHEN

《机械工程前沿（英文）》 2011年 第6卷 第3期   页码 344-353 doi: 10.1007/s11465-011-0227-x

摘要：

The motion dynamics and accuracy of parallel kinematic machines largely depend on the weights and rigidity of typical rigid links. Therefore, these parts should be designed in such a way that they are light but rigid. This work employs the techniques of topology and size optimization to design two typical rigid links of a parallel kinematic machine (PKM) and subsequently obtains applicable structures for them. The calculation models are established, and a new algorithm called the Guide-Weight method is introduced to solve topology optimization problems. The commercial software Ansys is used to perform size optimization.

关键词： topology optimization     size optimization     parallel kinematic machine (PKM)    

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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    

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标题 作者 时间 类型 操作

Synergistic optimization framework for the process synthesis and design of biorefineries

期刊论文

Recent advances in system reliability optimization driven by importance measures

Shubin SI, Jiangbin ZHAO, Zhiqiang CAI, Hongyan DUI

期刊论文

Split-order consolidation optimization for online supermarkets: Process analysis and optimization models

期刊论文

Design and optimization of reactive distillation: a review

期刊论文

Review on the design and optimization of hydrogen liquefaction processes

Liang YIN, Yonglin JU

期刊论文

Comparative seismic design optimization of spatial steel dome structures through three recent metaheuristic

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

Footholds optimization for legged robots walking on complex terrain

期刊论文

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

期刊论文

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

Yimin ZHANG

期刊论文

Discussion on the System Optimization of the Energy Development Strategy and Plan

Da-di Zhou

期刊论文

Robust isogeometric topology optimization for piezoelectric actuators with uniform manufacturability

期刊论文

Data analytics and optimization for smart industry

Lixin TANG, Ying MENG

期刊论文

Structural optimization of typical rigid links in a parallel kinematic machine

Xinjun LIU, Zhidong LI, Xiang CHEN

期刊论文

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

Yimin ZHANG

期刊论文