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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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Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

《结构与土木工程前沿（英文）》页码 976-989 doi: 10.1007/s11709-022-0840-2

摘要： Vibration-based damage detection methods have become widely used because of their advantages over traditional methods. This paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANN) combined with Butterfly Optimization Algorithm (BOA). ANN is quite successful in such identification issues, but it has some limitations, such as reduction of error after system training is complete, which means the output does not provide optimal results. This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN). Natural frequencies are used as input parameters and crack depth as output. The data are collected from improved FEM using simulation tools (ABAQUS) based on different crack depths and locations as the first stage. Next, data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique. The proposed approach, compared to other methods, can predict crack depth with improved accuracy.

关键词： damage prediction ANN BOA FEM experimental modal analysis

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Optimization of aero-engine pipeline for avoiding vibration based on length adjustment of straight-line

《机械工程前沿（英文）》 2022年第17卷第1期页码 11-11 doi: 10.1007/s11465-021-0667-x

摘要： In the design and troubleshooting of aero-engine pipeline, the vibration reduction of the pipeline system is often achieved by adjusting the hoop layout, provided that the shape of pipeline remains unchanged. However, in reality, the pipeline system with the best antivibration performance may be obtained only by adjusting the pipeline shape. In this paper, a typical spatial pipeline is taken as the research object, the length of straight-line segment is taken as the design variable, and an innovative optimization method of avoiding vibration of aero-engine pipeline is proposed. The relationship between straight-line segment length and parameters that determine the geometric characteristics of the pipeline, such as the position of key reference points, bending angle, and hoop position, are derived in detail. Based on this, the parametric finite element model of the pipeline system is established. Taking the maximum first-order natural frequency of pipeline as the optimization objective and introducing process constraints and vibration avoidance constraints, the optimization model of the pipeline system is established. The genetic algorithm and the golden section algorithm are selected to solve the optimization model, and the relevant solution procedure is described in detail. Finally, two kinds of pipelines with different total lengths are selected to carry out a case study. Based on the analysis of the influence of straight-line segment length on the vibration characteristics of the pipeline system, the optimization methods developed in this paper are demonstrated. Results show that the developed optimization method can obtain the optimal single value or interval of the straight-line segment length while avoiding the excitation frequency. In addition, the optimization efficiency of the golden section algorithm is remarkably higher than that of the genetic algorithm for length optimization of a single straight-line segment.

关键词： length adjustment spatial pipeline aero-engine vibration avoidance optimization genetic algorithm golden section algorithm

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A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

《能源前沿（英文）》 2020年第14卷第1期页码 139-151 doi: 10.1007/s11708-017-0484-4

摘要： In this paper, the genetic algorithm (GA) is applied to optimize a grid connected solar photovoltaic (PV)-wind-battery hybrid system using a novel energy filter algorithm. The main objective of this paper is to minimize the total cost of the hybrid system, while maintaining its reliability. Along with the reliability constraint, some of the important parameters, such as full utilization of complementary nature of PV and wind systems, fluctuations of power injected into the grid and the battery’s state of charge (SOC), have also been considered for the effective sizing of the hybrid system. A novel energy filter algorithm for smoothing the power injected into the grid has been proposed. To validate the proposed method, a detailed case study has been conducted. The results of the case study for different cases, with and without employing the energy filter algorithm, have been presented to demonstrate the effectiveness of the proposed sizing strategy.

关键词： PV-wind-battery hybrid system size optimization genetic algorithm

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Optimization of cold-end system of thermal power plants based on entropy generation minimization

《能源前沿（英文）》 2022年第16卷第6期页码 956-972 doi: 10.1007/s11708-021-0785-5

摘要： Cold-end systems are heat sinks of thermal power cycles, which have an essential effect on the overall performance of thermal power plants. To enhance the efficiency of thermal power plants, multi-pressure condensers have been applied in some large-capacity thermal power plants. However, little attention has been paid to the optimization of the cold-end system with multi-pressure condensers which have multiple parameters to be identified. Therefore, the design optimization methods of cold-end systems with single- and multi-pressure condensers are developed based on the entropy generation rate, and the genetic algorithm (GA) is used to optimize multiple parameters. Multiple parameters, including heat transfer area of multi-pressure condensers, steam distribution in condensers, and cooling water mass flow rate, are optimized while considering detailed entropy generation rate of the cold-end systems. The results show that the entropy generation rate of the multi-pressure cold-end system is less than that of the single-pressure cold-end system when the total condenser area is constant. Moreover, the economic performance can be improved with the adoption of the multi-pressure cold-end system. When compared with the single-pressure cold-end system, the excess revenues gained by using dual- and quadruple-pressure cold-end systems are 575 and 580 k$/a, respectively.

关键词： cold-end system entropy generation minimization optimization economic analysis genetic algorithm (GA)

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基于嵌入协作的多方法协作优化方法

罗文彩,罗世彬,王振国

《中国工程科学》 2004年第6卷第4期页码 51-55

摘要：

提出一种基于嵌入协作的多方法协作优化方法。算法采用嵌入方式组织各个优化方法之间的协作，利用优化方法之间的协作效应提高优化性能。进行遗传算法、模式搜索法和Powell法嵌入协作组成的多方法协作优化方法设计。计算实例表明，基于嵌入协作的多方法协作优化方法取得了优于单个优化方法的全局最优特性。

关键词：多方法协作优化方法嵌入协作遗传算法模式搜索法 Powell法

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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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工程项目管理多目标均衡优化研究综述

张连营,徐畅,吴琼

《中国工程科学》 2012年第14卷第11期页码 107-112

摘要：

寻求工程项目各目标之间的均衡最优是工程项目管理的重要方面，近年来相关研究发展迅速，已取得了较为丰硕的研究成果。本文通过文献研究，对该领域的研究现状进行了综述。分别从确定条件下的工程项目多目标均衡优化模型和不确定条件下的工程项目多目标均衡优化模型两个方面，对该领域的研究现状进行了分析，并展望了该领域的研究趋势和发展方向。旨在总结当前工程项目多目标均衡优化领域中的研究成果并揭示当前的热点研究问题，为今后研究提供一定的参考和建议。

关键词：工程项目项目管理多目标均衡优化智能优化算法

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用遗传算法求解供水泵站的效率优化问题

廖莉,林家恒,张承慧

《中国工程科学》 2002年第4卷第9期页码 54-58

摘要：

供水企业向来是城市的用电大户，其用电量主要体现在泵站水泵机组的电耗上。供水泵站的高效运行对节约电能、安全供水具有极为重要的意义。文章对供水泵站的效率优化问题进行了探讨，在提出用指数曲线准确地拟合水泵性能曲线的基础上，建立了供水栗站效率优化问题的数学模型，并设计了相应的遗传算法进行求解，仿真实验结果表明了该算法合理、有效。

关键词：供水泵站数值拟合优化遗传算法

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Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

《机械工程前沿（英文）》 2013年第8卷第4期页码 429-442 doi: 10.1007/s11465-013-0277-3

摘要：

Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

关键词： electrochemical machining process (ECM) modeling adaptive neuro-fuzzy inference system (ANFIS) optimization cuckoo optimization algorithm (COA)

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Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

《能源前沿（英文）》 2014年第8卷第4期页码 459-463 doi: 10.1007/s11708-014-0335-5

摘要： The operation condition of the cold-end system of a steam turbine has a direct impact on the economy and security of the unit as it is an indispensible auxiliary system of the thermal power unit. Many factors influence the cold-end operation of a steam turbine; therefore, the operation mode needs to be optimized. The optimization analysis of a 1000 MW ultra-supercritical (USC) unit, the turbine cold-end system, was performed utilizing the back propagation (BP) neural network method with genetic algorithm (GA) optimization analysis. The optimized condenser pressure under different conditions was obtained, and it turned out that the optimized parameters were of significance to the performance and economic operation of the system.

关键词： optimization turbine cold-end system BP neural network genetic algorithm

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网络设计问题的一种代理模型优化算法 Article

Meng LI, Xi LIN, Xi-qun CHEN

《信息与电子工程前沿（英文）》 2017年第18卷第11期页码 1693-1704 doi: 10.1631/FITEE.1601403

摘要：由于其双层规划结构本质上的非凸性，交通网络设计问题一直以来都是交通规划领域中最为困难的问题之一。尤其在考虑混合了连续变量与离散变量的决策变量时，得到的混合网络设计形式进一步增加了问题的难度。本文引入了一种代理模型优化算法，用以解决三种不同种类的网络设计问题，包括连续、离散与混合的情形。我们证明了提出的算法在解决连续网络设计问题时，能够确保“渐进完全收敛”的性质，即在给定足够长的计算时间时，算法能够以概率1收敛到全局最优解。为了展示本文提出的框架在实际问题中的表现，我们用大量的算例对比了代理模型算法与大量用于解决网络设计问题的经典算法、启发式算法的效果。结果表明，以效率与精确度而论，代理模型算法是其中最优秀之一，同时它还能够有效地解决超过20个变量的较大规模的问题。本文提出的代理模型优化框架也能够用于解决交通领域的其他优化问题。

关键词：网络设计问题；代理模型优化；交通规划；启发式算法

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Estimation of distribution algorithm enhanced particle swarm optimization for water distribution networkoptimization

Xuewei QI,Ke LI,Walter D. POTTER

《环境科学与工程前沿（英文）》 2016年第10卷第2期页码 341-351 doi: 10.1007/s11783-015-0776-z

摘要： The optimization of a water distribution network (WDN) is a highly nonlinear, multi-modal, and constrained combinatorial problem. Particle swarm optimization (PSO) has been shown to be a fast converging algorithm for WDN optimization. An improved estimation of distribution algorithm (EDA) using historic best positions to construct a sample space is hybridized with PSO both in sequential and in parallel to improve population diversity control and avoid premature convergence. Two water distribution network benchmark examples from the literature are adopted to evaluate the performance of the proposed hybrid algorithms. The experimental results indicate that the proposed algorithms achieved the literature record minimum (6.081 M$) for the small size Hanoi network. For the large size Balerma network, the parallel hybrid achieved a slightly lower minimum (1.921M?) than the current literature reported best minimum (1.923M?). The average number of evaluations needed to achieve the minimum is one order smaller than most existing algorithms. With a fixed, small number of evaluations, the sequential hybrid outperforms the parallel hybrid showing its capability for fast convergence. The fitness and diversity of the populations were tracked for the proposed algorithms. The track record suggests that constructing an EDA sample space with historic best positions can improve diversity control significantly. Parallel hybridization also helps to improve diversity control yet its effect is relatively less significant.

关键词： particle swarm optimization (PSO) diversity control estimation of distribution algorithm (EDA) water distribution network (WDN) premature convergence hybrid strategy

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Improved resilience measure for component recovery priority in power grids

《工程管理前沿（英文）》 2021年第8卷第4期页码 545-556 doi: 10.1007/s42524-021-0161-5

摘要： Given the complexity of power grids, the failure of any component may cause large-scale economic losses. Consequently, the quick recovery of power grids after disasters has become a new research direction. Considering the severity of power grid disasters, an improved power grid resilience measure and its corresponding importance measures are proposed. The recovery priority of failed components after a disaster is determined according to the influence of the failed components on the power grid resilience. Finally, based on the data from the 2019 Power Yearbook of each city in Shandong Province, China, the power grid resilience after a disaster is analyzed for two situations, namely, partial components failure and failure of all components. Result shows that the recovery priorities of components with different importance measures vary. The resilience evaluations under different repair conditions prove the feasibility of the proposed method.

关键词： resilience measure power grid importance measure component recovery

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Group-based multiple pipe routing method for aero-engine focusing on parallel layout

《机械工程前沿（英文）》 2021年第16卷第4期页码 798-813 doi: 10.1007/s11465-021-0645-3

摘要： External pipe routing for aero-engine in limited three-dimensional space is a typical nondeterministic polynomial hard problem, where the parallel layout of pipes plays an important role in improving the utilization of layout space, facilitating pipe assembly, and maintenance. This paper presents an automatic multiple pipe routing method for aero-engine that focuses on parallel layout. The compressed visibility graph construction algorithm is proposed first to determine rapidly the rough path and interference relationship of the pipes to be routed. Based on these rough paths, the information of pipe grouping and sequencing are obtained according to the difference degree and interference degree, respectively. Subsequently, a coevolutionary improved differential evolution algorithm, which adopts the coevolutionary strategy, is used to solve multiple pipe layout optimization problem. By using this algorithm, pipes in the same group share the layout space information with one another, and the optimal layout solution of pipes in this group can be obtained in the same evolutionary progress. Furthermore, to eliminate the minor angle deviation of parallel pipes that would cause assembly stress in actual assembly, an accurate parallelization processing method based on the simulated annealing algorithm is proposed. Finally, the simulation results on an aero-engine demonstrate the feasibility and effectiveness of the proposed method.

关键词： multiple pipe routing optimization algorithm aero-engine pipe grouping parallel layout

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标题作者时间类型操作

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

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

期刊论文

Optimization of aero-engine pipeline for avoiding vibration based on length adjustment of straight-line

期刊论文

A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system usingenergy filter algorithm

Aeidapu MAHESH, Kanwarjit Singh SANDHU

期刊论文

Optimization of cold-end system of thermal power plants based on entropy generation minimization

期刊论文

基于嵌入协作的多方法协作优化方法

罗文彩,罗世彬,王振国

期刊论文

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

期刊论文

工程项目管理多目标均衡优化研究综述

张连营,徐畅,吴琼

期刊论文

用遗传算法求解供水泵站的效率优化问题

廖莉,林家恒,张承慧

期刊论文

Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing

Reza TEIMOURI, Hamed SOHRABPOOR

期刊论文

Optimization of turbine cold-end system based on BP neural network and genetic algorithm

Chang CHEN,Danmei XIE,Yangheng XIONG,Hengliang ZHANG

期刊论文

网络设计问题的一种代理模型优化算法

Meng LI, Xi LIN, Xi-qun CHEN

期刊论文

Estimation of distribution algorithm enhanced particle swarm optimization for water distribution networkoptimization

Xuewei QI,Ke LI,Walter D. POTTER

期刊论文

Improved resilience measure for component recovery priority in power grids

期刊论文

Group-based multiple pipe routing method for aero-engine focusing on parallel layout

期刊论文

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