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A Pareto Strength SCE-UA Algorithm for ReservoirOptimization Operation

Lin Jianyi,Cheng Chuntian,Gu Yanping,Wu Xinyu

Strategic Study of CAE 2007, Volume 9, Issue 10,   Pages 80-82

Abstract:

In this paper,  the Pareto strength SCE-UA algorithm (PSSCE) is's comparing procedure and the population ranking procedure which are respectively based on the Paretodominance relationship and the Pareto strength definition.

Keywords： reservoir optimal operation     constrained optimization     Pareto dominate     Pareto strength     SCE-UA algorithm    

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

Ullah SAIF,Zailin GUAN,Baoxi WANG,Jahanzeb MIRZA

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 3,   Pages 257-264 doi: 10.1007/s11465-014-0294-x

Abstract: and solution of multi objective optimization problems exists in the form of a set of solutions called Paretosolutions and from these solutions it might be difficult to decide which Pareto solution can satisfymethod which is a recently introduced method in literature is extended in the current research for ParetoThe proposed method called Pareto lexicographic α-robust approach can define Pareto

Keywords： Pareto     lexicographic α-robust     assembly line balancing    

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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

Frontiers in Energy 2018, Volume 12, Issue 1,   Pages 109-120 doi: 10.1007/s11708-018-0540-8

Abstract: electrical current are optimized for a given system architecture, a “heat flux vs. temperature difference” Paretooptimization process, 3 pairs of master curves were generated, which were then used to compose the Pareto

Keywords： thermoelectric cooling     thermal management     optimization     high flux electronics    

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Evolutionary Algorithms for Multi-objective Optimization and Decision-Making Problems

Xie Tao Chen Huowang

Strategic Study of CAE 2002, Volume 4, Issue 2,   Pages 59-68

Abstract: The researches on multi-objective evolutionary algorithms (MOEA) focus mainly on the Pareto-based comparisonassignment and Riching techniques, etc., so that the population can converge and uniformly distribute in the Paretoand classification of multi-objective optimization and decision-making techniques, analyzes both the Pareto-basedand non-Pareto-based evolutionary algorithms, and,particularly,the five well-known MOEAs.problems related to the researches on MOEAs are addressed in details, such as the characteristics of Pareto

Keywords： evolutionary algorithms     multi-objective optimization and decision-making     Pareto optimal    

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

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

Frontiers in Energy 2015, Volume 9, Issue 1,   Pages 106-114 doi: 10.1007/s11708-014-0341-7

Abstract: 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.

Keywords： molten carbonate fuel cell (MCFC)     multi-objective optimization (MOO)     Pareto curve     genetic algorithm     CO    

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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

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 9,   Pages 1089-1103 doi: 10.1007/s11709-022-0851-z

Abstract: 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.

Keywords： retrofit     stiffness demand     drift concentration factor     multi-objective design     genetic algorithm     Pareto    

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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

Frontiers of Structural and Civil Engineering 2013, Volume 7, Issue 2,   Pages 117-126 doi: 10.1007/s11709-013-0205-y

Abstract: In the present study, evolutionary algorithms (EAs) are employed for multi-objective Pareto optimum designAlso, multi-objective EAs with a diversity preserving mechanism are used for Pareto optimization of suchTherefore, optimal Pareto fronts of such models are obtained in each case, which exhibit the trade-offs

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

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

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

Frontiers in Energy 2018, Volume 12, Issue 4,   Pages 518-528 doi: 10.1007/s11708-018-0594-7

Abstract: the non-dominated sorting generic algorithm II (NSGA-II) is employed to derive a set of non-dominated ParetoThe diversity of Pareto solutions is conserved by a crowding distance operator, and the best compromisedPareto solution is determined based on the fuzzy set theory.The results obtained from the numerical study indicate that the NSGA-II results in more diversified Pareto

Keywords： optimization     hybrid distributed energy system     non-dominated sorting generic algorithm II     fuzzy set theory     Pareto    

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Optimal signal design strategywith improper Gaussian signaling in the Z-interference channel Article

Dan LI, Shan WANG, Fang-lin GU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1900-1912 doi: 10.1631/FITEE.1700030

Abstract: We propose a thoroughly optimal signal design strategy to achieve the Pareto boundary (boundary of theSpecifically, we show that the Pareto boundary has two different schemes determined by the two pathsFinally, we provide an in-depth discussion of the structure of the Pareto boundary, characterized by

Keywords： Z-interference channel     Improper Gaussian signaling     Sum-rate     Pareto boundary     Covariance     Pseudo-covariance    

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A many-objective evolutionary algorithm based on decomposition with dynamic resource allocation for irregular optimization Research Articles

Ming-gang Dong, Bao Liu, Chao Jing,jingchao@glut.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 8,   Pages 1119-1266 doi: 10.1631/FITEE.1900321

Abstract: To address such issues, current approaches focus mainly on problems with regular Pareto front ratherallocate computing resources to different search areas according to different shapes of the problem’s Pareto

Keywords： Many-objective optimization problems     Irregular Pareto front     External archive     Dynamic resource allocation    

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Title Author Date Type Operation

A Pareto Strength SCE-UA Algorithm for ReservoirOptimization Operation

Lin Jianyi,Cheng Chuntian,Gu Yanping,Wu Xinyu

Journal Article

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

Ullah SAIF,Zailin GUAN,Baoxi WANG,Jahanzeb MIRZA

Journal Article

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

Journal Article

Evolutionary Algorithms for Multi-objective Optimization and Decision-Making Problems

Xie Tao Chen Huowang

Journal Article

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

Ramin ROSHANDEL,Majid ASTANEH,Farzin GOLZAR

Journal Article

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

Journal Article

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

Journal Article

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

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

Journal Article

Optimal signal design strategywith improper Gaussian signaling in the Z-interference channel

Dan LI, Shan WANG, Fang-lin GU

Journal Article

A many-objective evolutionary algorithm based on decomposition with dynamic resource allocation for irregular optimization

Ming-gang Dong, Bao Liu, Chao Jing,jingchao@glut.edu.cn

Journal Article