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Multi-objective optimization in a finite time thermodynamic method for dish-Stirling by branch and boundmethod and MOPSO algorithm

Mohammad Reza NAZEMZADEGAN, Alibakhsh KASAEIAN, Somayeh TOGHYANI, Mohammad Hossein AHMADI, R. SAIDUR, Tingzhen MING

《能源前沿（英文）》 2020年 第14卷 第3期   页码 649-665 doi: 10.1007/s11708-018-0548-0

摘要： There are various analyses for a solar system with the dish-Stirling technology. One of those analyses is the finite time thermodynamic analysis by which the total power of the system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders, and cold side heat exchanger have been considered. During this investigation, four objective functions have been optimized simultaneously, including power, efficiency, entropy, and economic factors. In addition to the four-objective optimization, three-objective, two-objective, and single-objective optimizations have been done on the dish-Stirling model. The algorithm of multi-objective particle swarm optimization (MOPSO) with post-expression of preferences is used for multi-objective optimizations while the branch and bound algorithm with pre-expression of preferences is used for single-objective and multi-objective optimizations. In the case of multi-objective optimizations with post-expression of preferences, Pareto optimal front are obtained, afterward by implementing the fuzzy, LINMAP, and TOPSIS decision making algorithms, the single optimum results can be achieved. The comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite time thermodynamic equations.

关键词： dish-Stirling     finite time model     branch and bound algorithm     multi-objective particle swarm optimization (MOPSO)    

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基于多目标粒子群协同算法的状态参数优化

丁雷,吴敏,佘锦华,段平

《中国工程科学》 2010年 第12卷 第2期   页码 101-107

摘要：

针对铅锌烧结过程综合透气性、烧结终点的优化具有强非线性、计算复杂等特点，提出了一种有效的多目标粒子群协同优化算法。首先，建立了有综合透气性、烧结终点两个目标的优化模型。接着，通过改进的约束比较方法、粒子极值选取方法，以及利用不同的粒子群来分别优化相应的变量，提出了一种改进的多目标粒子群协同优化算法。最后，利用提出的多目标优化算法进行综合透气性、烧结终点的优化。仿真结果表明，所提出的多目标优化算法能较好地解决综合透气性、烧结终点的优化问题。

关键词： 铅锌烧结过程     综合透气性     烧结终点     多目标粒子群协同优化算法    

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Attuned design of demand response program and M-FACTS for relieving congestion in a restructured market environment

Y. HASHEMI,H. SHAYEGHI,B. HASHEMI

《能源前沿（英文）》 2015年 第9卷 第3期   页码 282-296 doi: 10.1007/s11708-015-0366-6

摘要： This paper addresses the attuned use of multi-converter flexible alternative current transmission systems (M-FACTS) devices and demand response (DR) to perform congestion management (CM) in the deregulated environment. The strong control capability of the M-FACTS offers a great potential in solving many of the problems facing electric utilities. Besides, DR is a novel procedure that can be an effective tool for reduction of congestion. A market clearing procedure is conducted based on maximizing social welfare (SW) and congestion as network constraint is paid by using concurrently the DR and M-FACTS. A multi-objective problem (MOP) based on the sum of the payments received by the generators for changing their output, the total payment received by DR participants to reduce their load and M-FACTS cost is systematized. For the solution of this problem a nonlinear time-varying evolution (NTVE) based multi-objective particle swarm optimization (MOPSO) style is formed. Fuzzy decision-making (FDM) and technique for order preference by similarity to ideal solution (TOPSIS) approaches are employed for finding the best compromise solution from the set of Pareto-solutions obtained through multi-objective particle swarm optimization-nonlinear time-varying evolution (MOPSO-NTVE). In a real power system, Azarbaijan regional power system of Iran, comparative analysis of the results obtained from the application of the DR & unified power flow controller (UPFC) and the DR & M-FACTS are presented.

关键词： multi-converter flexible alternative current transmission systems (M-FACTS)     demand response     fuzzy decision making     multi-objective particle swarm optimization-nonlinear time-varying evolution (MOPSO-NTVE)    

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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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Fatigue and impact analysis and multi-objective optimization design of Mg/Al assembled wheel considering

《机械工程前沿（英文）》 2022年 第17卷 第3期 doi: 10.1007/s11465-022-0701-7

摘要： The multi-material assembled light alloy wheel presents an effective lightweight solution for new energy vehicles, but its riveting connection remains a problem. To address this problem, this paper proposed the explicit riveting-implicit springback-implicit fatigue/explicit impact sequence coupling simulation analysis method, analyzed the fatigue and impact performance of the punching riveting connected magnesium/aluminum alloy (Mg/Al) assembled wheel, and constructed some major evaluation indicators. The accuracy of the proposed simulation method was verified by conducting physical experiments of single and cross lap joints. The punching riveting process parameters of the assembled wheel joints were defined as design variables, and the fatigue and impact performance of the assembled wheel was defined as the optimization objective. The connection-performance integration multi-objective optimization design of the assembled wheel considering riveting residual stress was designed via Taguchi experiment, grey relational analysis, analytic hierarchy process, principal component analysis, and entropy weighting methods. The optimization results of the three weighting methods were compared, and the optimal combination of design variables was determined. The fatigue and impact performance of the Mg/Al assembled wheel were effectively improved after optimization.

关键词： magnesium/aluminum assembled wheel     riveting residual stress     fatigue analysis     impact analysis     multi-objective optimization    

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Multi-objective optimization of surface texture for the slipperswash plate interface in EHA pumps

《机械工程前沿（英文）》 2022年 第17卷 第4期 doi: 10.1007/s11465-022-0704-4

摘要： Well-designed surface textures can improve the tribological properties and the efficiency of the electro-hydrostatic actuator (EHA) pump under high-speed and high-pressure conditions. This study proposes a multi-objective optimization model to obtain the arbitrarily surface textures design of the slipper/swash plate interface for improving the mechanical and volumetric efficiency of the EHA pump. The model is composed of the lubrication film model, the component dynamic model considering the spinning motion, and the multi-objective optimization model. In this way, the arbitrary-shaped surface texture with the best comprehensive effect in the EHA pump is achieved and its positive effects in the EHA pump prototype are verified. Experimental results show a reduction in wear and an improvement in mechanical and volumetric efficiency by 1.4% and 0.8%, respectively, with the textured swash plate compared with the untextured one.

关键词： electro-hydrostatic actuator     axial piston pump     slipper/swash plate interface     multi-objective optimization     surface texture    

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使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器 Article

null

《信息与电子工程前沿（英文）》 2017年 第18卷 第3期   页码 394-409 doi: 10.1631/FITEE.1500317

摘要： 由于多目标粒子群优化算法（Multi-objective particle swarm optimization, MOPSO）在解决非线性目标问题上具有较高性能，已被用于这一优化问题中。本文对所提出的HANFISC-TCSC效能进行了精确评估，并在两个不同的互联电力系统（即双区域水柴油热和三区域水热发电系统）中，将其与传统的MOPSO-TCSC算法进行了对比。两个电力系统中仿真结果表明都可明确证实，与传统MOPSO-TCSC算法相比，HANFISC-TCSC具有更高性能。

关键词： 分层自适应神经模糊推理系统控制器；晶闸管控制串联电容器补偿技术；自动发电控制（AGC）；多目标粒子群优化算法；电力系统动态稳定性；相互联系的多源电力系统    

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Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity

Yilei Lu, Yunqing Huang, Siyu Zeng, Can Wang

《环境科学与工程前沿（英文）》 2020年 第14卷 第2期 doi: 10.1007/s11783-019-1200-x

摘要： Impact of urban development on water system is assessed with carrying capacity. Impacts on both water resource quantity and environmental quality are involved. Multi-objective optimization revealing system trade-off facilitate the regulation. Efficiency, scale and structure of urban development are regulated in two stages. A roadmap approaching more sustainable development is provided for the case city. Environmental impact assessments and subsequent regulation measures of urban development plans are critical to human progress toward sustainability, since these plans set the scale and structure targets of future socioeconomic development. A three-step methodology for assessing and optimizing an urban development plan focusing on its impacts on the water system was developed. The methodology first predicted the pressure on the water system caused by implementation of the plan under distinct scenarios, then compared the pressure with the carrying capacity threshold to verify the system status; finally, a multi-objective optimization method was used to propose regulation solutions. The methodology enabled evaluation of the water system carrying state, taking socioeconomic development uncertainties into account, and multiple sets of improvement measures under different decisionmaker preferences were generated. The methodology was applied in the case of Zhoushan city in South-east China. The assessment results showed that overloading problems occurred in 11 out of the 13 zones in Zhoushan, with the potential pressure varying from 1.1 to 18.3 times the carrying capacity. As a basic regulation measure, an environmental efficiency upgrade could relieve the overloading in 4 zones and reduce 9%‒63% of the pressure. The optimization of industrial development showed that the pressure could be controlled under the carrying capacity threshold if the planned scale was reduced by 24% and the industrial structure was transformed. Various regulation schemes including a more suitable scale and structure with necessary efficiency standards are provided for decisionmakers that can help the case city approach a more sustainable development pattern.

关键词： Urban development plan     Urban water system     Carrying capacity     Scenario analysis     Multi-objective optimization    

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Uncertain and multi-objective programming models for crop planting structure optimization

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

《农业科学与工程前沿（英文）》 2016年 第3卷 第1期   页码 34-45 doi: 10.15302/J-FASE-2016084

摘要： Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP) model and an inexact fuzzy linear programming (IFLP) model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods of each model are expounded. Detailed analysis of results of each model and their comparisons demonstrate the feasibility and applicability of the models developed, therefore decision makers can choose the appropriate model when making decisions.

关键词： crop planting structure     optimization model     uncertainty     multi-objective    

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Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

《机械工程前沿（英文）》 2014年 第9卷 第4期   页码 354-367 doi: 10.1007/s11465-014-0319-5

摘要：

To improve the dynamic performance and reduce the weight of the planet carrier in wind turbine gearbox, a multi-objective optimization method, which is driven by the maximum deformation, the maximum stress and the minimum mass of the studied part, is proposed by combining the response surface method and genetic algorithms in this paper. Firstly, the design points’ distribution for the design variables of the planet carrier is established with the central composite design (CCD) method. Then, based on the computing results of finite element analysis (FEA), the response surface analysis is conducted to find out the proper sets of design variable values. And a multi-objective genetic algorithm (MOGA) is applied to determine the direction of optimization. As well, this method is applied to design and optimize the planet carrier in a 1.5 MW wind turbine gearbox, the results of which are validated by an experimental modal test. Compared with the original design, the mass and the stress of the optimized planet carrier are respectively reduced by 9.3% and 40%. Consequently, the cost of planet carrier is greatly reduced and its stability is also improved.

关键词： planet carrier     multi-objective optimization     genetic algorithms     wind turbine gearbox     modal experiment    

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Multi-objective optimization of molten carbonate fuel cell system for reducing CO

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

《能源前沿（英文）》 2015年 第9卷 第1期   页码 106-114 doi: 10.1007/s11708-014-0341-7

摘要： The aim of this paper is to investigate the implementation of a molten carbonate fuel cell (MCFC) as a CO separator. By applying multi-objective optimization (MOO) using the genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. Objective functions are minimization of the cost of electricity (COE) and minimization of CO emission rate. CO tax that is accounted as the pollution-related cost, transforming the environmental objective to the cost function. The results show that the MCFC stack which is fed by the syngas and gas turbine exhaust, not only reduces CO emission rate, but also produces electricity and reduces environmental cost of the system.

关键词： molten carbonate fuel cell (MCFC)     multi-objective optimization (MOO)     Pareto curve     genetic algorithm     CO2 separation    

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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    

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A new technique for solving the multi-objective optimization problem using hybrid approach

Mimoun YOUNES,Khodja FOUAD,Belabbes BAGDAD

《能源前沿（英文）》 2014年 第8卷 第4期   页码 490-503 doi: 10.1007/s11708-014-0311-0

摘要： Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a bi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach (firefly algorithm-real genetic algorithm, FFA-RGA) has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi-objective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.

关键词： economic power dispatch (EPD)     firefly algorithm (FFA)     real genetic algorithm (RGA)     hybrid method    

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Optimal design analysis of a tubular heat exchanger network with extended surfaces using multi-objectiveconstructal optimization

Hassan HAJABDOLLAHI, Mohammad SHAFIEY DEHAJ, Babak MASOUMPOUR, Mohammad ATAEIZADEH

《能源前沿（英文）》 2022年 第16卷 第5期   页码 862-875 doi: 10.1007/s11708-022-0839-3

摘要： The present work aims to investigate the influence of extended surfaces (fins) on the multi-objective optimization of a tubular heat exchanger network (THEN). An increase in the heat transfer area using various extended surfaces (fins) to enhance the performance of the heat exchanger was used while considering the effectiveness and total heat transfer area as two objective functions. In addition to the simulation of simple fins, a new set of fins, called constructal fins, was designed based on the constructal theory. Tubular heat exchanger network design parameters were chosen as optimization variables, and optimization results were achieved in such a way as to enhance the effectiveness and decrease the total heat transfer area. The results show the importance of constructal fins in improving the objective functions of heat exchangers. For instance, the simple fins case enhances the effectiveness by up to 5.3% compared to that without fins (usual heat exchanger) while using constructal fins, in addition to the 7% increment of effectiveness, reduces the total heat transfer area by 9.47%. In order to optimize the heat exchanger, the heat transfer rate and cold fluid temperature must increase, and at the same time, the hot exiting fluid temperature should decrease at the same constant total heat transfer area, which is higher in the constructal fins case. Finally, optimized design variables were studied for different cases, and the effects of various fins were reported.

关键词： constructal theory     extended surface     effectiveness     total heat transfer area     multi-objective optimization    

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多目标优化与决策问题的演化算法

谢涛,陈火旺

《中国工程科学》 2002年 第4卷 第2期   页码 59-68

摘要：

近年来，多目标优化与决策问题求解已成为演化计算的一个重要研究方向。为使演化算法的种群解 能尽快收敛并均匀分布于多目标问题的非劣最优域，多目标演化算法的研究热点集中在基于Pareto最优概念的 种群个体的比较与排序、适应值賦值与小生境技术等方面。介绍了多目标优化与决策技术的发展历史与分类方 法，分析了基于Pareto最优概念与不基于Pareto最优概念两大类的多目标演化算法，并详细比较与分析了几种 典型多目标演化算法。其次，论述了与多目标演化算法研究紧密相关的一些问题，如多目标问题解的性质，测 试函数集设计，算法性能评估技术，算法收敛性，并行实现以及实际多目标优化问题的处理等。

关键词： 演化计算     多目标优化与决策     Pareto最优    

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标题 作者 时间 类型 操作

Multi-objective optimization in a finite time thermodynamic method for dish-Stirling by branch and boundmethod and MOPSO algorithm

Mohammad Reza NAZEMZADEGAN, Alibakhsh KASAEIAN, Somayeh TOGHYANI, Mohammad Hossein AHMADI, R. SAIDUR, Tingzhen MING

期刊论文

基于多目标粒子群协同算法的状态参数优化

丁雷,吴敏,佘锦华,段平

期刊论文

Attuned design of demand response program and M-FACTS for relieving congestion in a restructured market environment

Y. HASHEMI,H. SHAYEGHI,B. HASHEMI

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

Fatigue and impact analysis and multi-objective optimization design of Mg/Al assembled wheel considering

期刊论文

Multi-objective optimization of surface texture for the slipperswash plate interface in EHA pumps

期刊论文

使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器

null

期刊论文

Scenario-based assessment and multi-objective optimization of urban development plan with carrying capacity

Yilei Lu, Yunqing Huang, Siyu Zeng, Can Wang

期刊论文

Uncertain and multi-objective programming models for crop planting structure optimization

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

期刊论文

Multi-objective genetic algorithms based structural optimization and experimental investigation of the

Pengxing YI,Lijian DONG,Tielin SHI

期刊论文

Multi-objective optimization of molten carbonate fuel cell system for reducing CO

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

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

A new technique for solving the multi-objective optimization problem using hybrid approach

Mimoun YOUNES,Khodja FOUAD,Belabbes BAGDAD

期刊论文

Optimal design analysis of a tubular heat exchanger network with extended surfaces using multi-objectiveconstructal optimization

Hassan HAJABDOLLAHI, Mohammad SHAFIEY DEHAJ, Babak MASOUMPOUR, Mohammad ATAEIZADEH

期刊论文

多目标优化与决策问题的演化算法

谢涛,陈火旺

期刊论文