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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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Compressive strength prediction and optimization design of sustainable concrete based on squirrel searchalgorithm-extreme gradient boosting technique

《结构与土木工程前沿（英文）》   页码 1310-1325 doi: 10.1007/s11709-023-0997-3

摘要： Concrete is the most commonly used construction material. However, its production leads to high carbon dioxide (CO2) emissions and energy consumption. Therefore, developing waste-substitutable concrete components is necessary. Improving the sustainability and greenness of concrete is the focus of this research. In this regard, 899 data points were collected from existing studies where cement, slag, fly ash, superplasticizer, coarse aggregate, and fine aggregate were considered potential influential factors. The complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength difficult. Instead of the traditional compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blast furnace slag. The intelligent prediction models were assessed using the root mean square error (RMSE), coefficient of determination (R2), mean absolute error (MAE), and variance accounted for (VAF). The results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded the best overall prediction performance with R2 values of 0.9930 and 0.9576, VAF values of 99.30 and 95.79, MAE values of 0.52 and 2.50, RMSE of 1.34 and 3.31 for the training and testing sets, respectively. The remaining five prediction methods yield promising results. Therefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green concrete. Finally, the developed SSA-XGB considered the effects of all the input factors on the compressive strength. The ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词： sustainable concrete     fly ash     slay     extreme gradient boosting technique     squirrel search algorithm     parametric 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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Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sortinggenetic algorithm-II

《结构与土木工程前沿（英文）》   页码 1428-1441 doi: 10.1007/s11709-023-0998-2

摘要： High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration. Therefore, effective and low-cost anti-seismic engineering measures must be designed for protection. An intake tower in northwest China was considered the research object, and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model. The non-dominated sorting genetic algorithm-II (NSGA-II) was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost. Finally, the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set, and recommendations for improvement were proposed. The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.

关键词： intake tower     NSGA-II     mode decomposition response spectrum method     anti-seismic engineering measures     optimization design     variable project cost    

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

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

《结构与土木工程前沿（英文）》 2022年 第16卷 第8期   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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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 and simultaneous heat integration design of a coal-based ethylene glycol refining processby a parallel differential evolution algorithm

《化学科学与工程前沿（英文）》 2023年 第17卷 第9期   页码 1280-1288 doi: 10.1007/s11705-023-2301-4

摘要： Coal to ethylene glycol still lacks algorithm optimization achievements for distillation sequencing due to high-dimension and strong nonconvexity characteristics, although there are numerous reports on horizontal comparisons and process revamping. This scenario triggers the navigation in this paper into the simultaneous optimization of parameters and heat integration of the coal to ethylene glycol distillation scheme and double-effect superstructure by the self-adapting dynamic differential evolution algorithm. To mitigate the influence of the strong nonconvexity, a redistribution strategy is adopted that forcibly expands the population search domain by exerting external influence and then shrinks it again to judge the global optimal solution. After two redistributive operations under the parallel framework, the total annual cost and CO2 emissions are 0.61%/1.85% better for the optimized process and 3.74%/14.84% better for the superstructure than the sequential optimization. However, the thermodynamic efficiency of sequential optimization is 11.63% and 10.34% higher than that of simultaneous optimization. This study discloses the unexpected great energy-saving potential for the coal to ethylene glycol process that has long been unknown, as well as the strong ability of the self-adapting dynamic differential evolution algorithm to optimize processes described by the high-dimensional mathematical model.

关键词： ethylene glycol     redistribution     heat integration     optimization     parallel framework    

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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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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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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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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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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

Compressive strength prediction and optimization design of sustainable concrete based on squirrel searchalgorithm-extreme gradient boosting technique

期刊论文

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

期刊论文

Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sortinggenetic algorithm-II

期刊论文

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

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

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 and simultaneous heat integration design of a coal-based ethylene glycol refining processby a parallel differential evolution algorithm

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

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

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

Improved resilience measure for component recovery priority in power grids

期刊论文