资源类型

期刊论文 10

年份

2022 1

2020 1

2018 2

2017 1

2015 1

2014 1

2013 1

2007 1

2002 1

展开 ︾

关键词

Pareto 优于关系 1

Pareto 强度值 1

Pareto最优 1

SCE-UA算法 1

Z干扰信道;非正则信号;和速率;帕累托边界;协方差;伪协方差 1

多目标优化与决策 1

水库优化调度 1

演化计算 1

约束优化 1

高维多目标优化问题;不规则帕累托前沿;外部存档;动态资源分配;转化的密度评估方法;切比雪夫分解方法 1

展开 ︾

检索范围:

排序: 展示方式:

水库优化调度的Pareto强度值SCE-UA算法

林剑艺,程春田,顾妍平,武新宇

《中国工程科学》 2007年 第9卷 第10期   页码 80-82

摘要:

提出求解水库优化调度问题的Pareto强度值SCE-UA算法,该方法将水库优化调度的约束优化问题转换成两个目标函数的无约束优化问题,一个为原问题的目标函数,另一个为违反约束条件的程度函数;对上述两个目标函数组成的向量个体,利用Pareto 优于关系和个体Pareto 强度值概念,实现个体的优劣比较和群体的优劣排序,在此基础上使用 SCE-UA算法求解。

关键词: 水库优化调度     约束优化     Pareto 优于关系     Pareto 强度值     SCE-UA算法    

Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing

null

《机械工程前沿(英文)》 2014年 第9卷 第3期   页码 257-264 doi: 10.1007/s11465-014-0294-x

摘要:

Robustness in most of the literature is associated with min-max or min-max regret criteria. However, these criteria of robustness are conservative and therefore recently new criteria called, lexicographic α-robust method has been introduced in literature which defines the robust solution as a set of solutions whose quality or jth largest cost is not worse than the best possible jth largest cost in all scenarios. These criteria might be significant for robust optimization of single objective optimization problems. However, in real optimization problems, two or more than two conflicting objectives are desired to optimize concurrently and solution of multi objective optimization problems exists in the form of a set of solutions called Pareto solutions and from these solutions it might be difficult to decide which Pareto solution can satisfy min-max, min-max regret or lexicographic α-robust criteria by considering multiple objectives simultaneously. Therefore, lexicographic α-robust method which is a recently introduced method in literature is extended in the current research for Pareto solutions. The proposed method called Pareto lexicographic α-robust approach can define Pareto lexicographic α-robust solutions from different scenarios by considering multiple objectives simultaneously. A simple example and an application of the proposed method on a simple problem of multi objective optimization of simple assembly line balancing problem with task time uncertainty is presented to get their robust solutions. The presented method can be significant to implement on different multi objective robust optimization problems containing uncertainty.

关键词: Pareto     lexicographic α-robust     assembly line balancing    

System-level Pareto frontiers for on-chip thermoelectric coolers

Sevket U. YURUKER, Michael C. FISH, Zhi YANG, Nicholas BALDASARO, Philip BARLETTA, Avram BAR-COHEN, Bao YANG

《能源前沿(英文)》 2018年 第12卷 第1期   页码 109-120 doi: 10.1007/s11708-018-0540-8

摘要: The continuous rise in heat dissipation of integrated circuits necessitates advanced thermal solutions to ensure system reliability and efficiency. Thermoelectric coolers are among the most promising techniques for dealing with localized on-chip hot spots. This study focuses on establishing a holistic optimization methodology for such thermoelectric coolers, in which a thermoelectric element’s thickness and the electrical current are optimized to minimize source temperature with respect to ambient, when the thermal and electrical parasitic effects are considered. It is found that when element thickness and electrical current are optimized for a given system architecture, a “heat flux vs. temperature difference” Pareto frontier curve is obtained, indicating that there is an optimum thickness and a corresponding optimum current that maximize the achievable temperature reduction while removing a particular heat flux. This methodology also provides the possible system level Δ ’s that can be achieved for a range of heat fluxes, defining the upper limits of thermoelectric cooling for that architecture. In this study, use was made of an extensive analytical model, which was verified using commercially available finite element analysis software. Through the optimization process, 3 pairs of master curves were generated, which were then used to compose the Pareto frontier for any given system architecture. Finally, a case study was performed to provide an in-depth demonstration of the optimization procedure for an example application.

关键词: thermoelectric cooling     thermal management     optimization     high flux electronics    

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: 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。

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

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    

A multi-objective design method for seismic retrofitting of existing reinforced concrete frames using pin-supported rocking walls

Yue CHEN; Rong XU; Hao WU; Tao SHENG

《结构与土木工程前沿(英文)》 2022年 第16卷 第9期   页码 1089-1103 doi: 10.1007/s11709-022-0851-z

摘要: Over the past several decades, a variety of technical ways have been developed in seismic retrofitting of existing reinforced concrete frames (RFs). Among them, pin-supported rocking walls (PWs) have received much attentions to researchers recently. However, it is still a challenge that how to determine the stiffness demand of PWs and assign the value of the drift concentration factor (DCF) for entire systems rationally and efficiently. In this paper, a design method has been exploited for seismic retrofitting of existing RFs using PWs (RF-PWs) via a multi-objective evolutionary algorithm. Then, the method has been investigated and verified through a practical project. Finally, a parametric analysis was executed to exhibit the strengths and working mechanism of the multi-objective design method. To sum up, the findings of this investigation show that the method furnished in this paper is feasible, functional and can provide adequate information for determining the stiffness demand and the value of the DCF for PWs. Furthermore, it can be applied for the preliminary design of these kinds of structures.

关键词: pin-supported rocking wall     reinforced concrete frame     seismic retrofit     stiffness demand     drift concentration factor     multi-objective design     genetic algorithm     Pareto optimal solution    

Predicting beach profile evolution with group method data handling-type neural networks on beaches with seawalls

M. A. LASHTEH NESHAEI, M. A. MEHRDAD, N. ABEDIMAHZOON, N. ASADOLLAHI

《结构与土木工程前沿(英文)》 2013年 第7卷 第2期   页码 117-126 doi: 10.1007/s11709-013-0205-y

摘要: A major goal of coastal engineering is to develop models for the reliable prediction of short- and long-term near shore evolution. The most successful coastal models are numerical models, which allow flexibility in the choice of initial and boundary conditions. In the present study, evolutionary algorithms (EAs) are employed for multi-objective Pareto optimum design of group method data handling (GMDH)-type neural networks that have been used for bed evolution modeling in the surf zone for reflective beaches, based on the irregular wave experiments performed at the Hydraulic Laboratory of Imperial College (London, UK). The input parameters used for such modeling are significant wave height, wave period, wave action duration, reflection coefficient, distance from shoreline and sand size. In this way, EAs with an encoding scheme are presented for evolutionary design of the generalized GMDH-type neural networks, in which the connectivity configurations in such networks are not limited to adjacent layers. Also, multi-objective EAs with a diversity preserving mechanism are used for Pareto optimization of such GMDH-type neural networks. The most important objectives of GMDH-type neural networks that are considered in this study are training error (TE), prediction error (PE), and number of neurons ( ). Different pairs of these objective functions are selected for two-objective optimization processes. Therefore, optimal Pareto fronts of such models are obtained in each case, which exhibit the trade-offs between the corresponding pair of the objectives and, thus, provide different non-dominated optimal choices of GMDH-type neural network model for beach profile evolution. The results showed that the present model has been successfully used to optimally prediction of beach profile evolution on beaches with seawalls.

关键词: beach profile evolution     genetic algorithms     group method of data handling     Pareto     reflective beaches    

Multi-objective optimization of a hybrid distributed energy system using NSGA-II algorithm

Hongbo REN, Yinlong LU, Qiong WU, Xiu YANG, Aolin ZHOU

《能源前沿(英文)》 2018年 第12卷 第4期   页码 518-528 doi: 10.1007/s11708-018-0594-7

摘要:

In this paper, a multi-objective optimization model is established for the investment plan and operation management of a hybrid distributed energy system. Considering both economic and environmental benefits, the overall annual cost and emissions of CO2 equivalents are selected as the objective functions to be minimized. In addition, relevant constraints are included to guarantee that the optimized system is reliable to satisfy the energy demands. To solve the optimization model, the non-dominated sorting generic algorithm II (NSGA-II) is employed to derive a set of non-dominated Pareto solutions. The diversity of Pareto solutions is conserved by a crowding distance operator, and the best compromised Pareto solution is determined based on the fuzzy set theory. As an illustrative example, a hotel building is selected for study to verify the effectiveness of the optimization model and the solving algorithm. The results obtained from the numerical study indicate that the NSGA-II results in more diversified Pareto solutions and the fuzzy set theory picks out a better combination of device capacities with reasonable operating strategies.

关键词: multi-objective optimization     hybrid distributed energy system     non-dominated sorting generic algorithm II     fuzzy set theory     Pareto optimal solution    

Z干扰信道下非正则信号的最佳设计策略 Article

Dan LI, Shan WANG, Fang-lin GU

《信息与电子工程前沿(英文)》 2017年 第18卷 第11期   页码 1900-1912 doi: 10.1631/FITEE.1700030

摘要: 本文提出一种用于在干扰被视为加性高斯噪声的假设下在Z干扰信道(z-interference channel, Z-IC)上实现非正则高斯信号(IGS)的Pareto边界(可实现速率区域的边界)。

关键词: Z干扰信道;非正则信号;和速率;帕累托边界;协方差;伪协方差    

不规则优化问题中基于动态资源分配的高维多目标优化算法 Research Articles

董明刚1,2,刘宝1,敬超1,2,3

《信息与电子工程前沿(英文)》 2020年 第21卷 第8期   页码 1119-1266 doi: 10.1631/FITEE.1900321

摘要: 多目标优化问题广泛存在于高速列车头形设计、重叠社区检测、电力调度等领域。为解决这类问题,目前方法主要集中于求解具有规则性帕累托前沿的问题,而非具有不规则帕累托前沿的问题。针对这种情况,提出一种基于动态资源分配分解的高维多目标进化算法(MaOEA/D-DRA)进行不规则优化。该算法能够根据问题的帕累托前沿形状,将计算资源动态分配到不同搜索区域。在搜索过程中使用进化种群和外部存档,从外部存档中提取的信息用于引导进化种群到不同搜索区域。进化种群采用切比雪夫方法将问题分解为若干子问题,并以协作方式优化所有子问题。采用转化的密度估计方法更新外部档案。将所提算法与5种最先进的多目标进化算法对比。实验结果表明,所提算法在收敛速度和种群成员多样性方面优于5种对比算法。与加权和方法和基于惩罚的边界相交方法比较,将切比切夫方法集成到算法中,对性能有一定提高。

关键词: 高维多目标优化问题;不规则帕累托前沿;外部存档;动态资源分配;转化的密度评估方法;切比雪夫分解方法    

标题 作者 时间 类型 操作

水库优化调度的Pareto强度值SCE-UA算法

林剑艺,程春田,顾妍平,武新宇

期刊论文

Pareto lexicographic α-robust approach and its application in robust multi objective assembly line balancing

null

期刊论文

System-level Pareto frontiers for on-chip thermoelectric coolers

Sevket U. YURUKER, Michael C. FISH, Zhi YANG, Nicholas BALDASARO, Philip BARLETTA, Avram BAR-COHEN, Bao YANG

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

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

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

期刊论文

A multi-objective design method for seismic retrofitting of existing reinforced concrete frames using pin-supported rocking walls

Yue CHEN; Rong XU; Hao WU; Tao SHENG

期刊论文

Predicting beach profile evolution with group method data handling-type neural networks on beaches with seawalls

M. A. LASHTEH NESHAEI, M. A. MEHRDAD, N. ABEDIMAHZOON, N. ASADOLLAHI

期刊论文

Multi-objective optimization of a hybrid distributed energy system using NSGA-II algorithm

Hongbo REN, Yinlong LU, Qiong WU, Xiu YANG, Aolin ZHOU

期刊论文

Z干扰信道下非正则信号的最佳设计策略

Dan LI, Shan WANG, Fang-lin GU

期刊论文

不规则优化问题中基于动态资源分配的高维多目标优化算法

董明刚1,2,刘宝1,敬超1,2,3

期刊论文