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Evolutionary algorithms for solving single- and multiple-objective political redistricting problems: The case study of Poland

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APPLIED SOFT COMPUTING 2024年 152卷

作者： Tomczyk, Michal K. Kadzinski, Milosz Poznan Univ Tech Inst Comp Sci PL-60965 Poznan Poland

We propose novel evolutionary algorithms for solving single- and multi -objective political redistricting problems. The objectives include population equality, compactness of districts, deviation from the current districting, and an expected number of mandates attainable by some parties. The former two ensure the constructed solutions are reasonable, while the latter pair is meaningful for the post -analysis on how the alternation of existing districts may affect election outcomes. We operate on data concerning geography, demography, and politics in Poland. The experiments reveal that our algorithms efficiently handle the fourobjective variant of the problem. In a single test run, we evaluate around one million solutions in nearly two hours on an average class computer, which is satisfactory given the problem's complexity. The methods construct high -quality non -dominated solutions, outperforming the current districting and revealing the tradeoffs between the objectives. The post -analysis allows us to observe connections between the expected number of mandates and the remaining three objectives. Specifically, attaining a greater number of mandates requires more significant changes in delineating the districts and potential violations of constraints. We also exhibit that the space for possible political manipulations increases when more districts can be determined.

关键词： Political redistricting Evolutionary algorithms multiple-objective optimization Gerrymandering Voting systems

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Failure Mode and Effect Analysis (FMEA) Approach Based on Avoidance of Aggregation Discrepancy

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IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 2023年 71卷 7325页

作者： Zha, Quanbo Wang, Sen Zhang, Wei Zhang, Hengjie Chongqing Univ Sch Management Sci & Real Estate Chongqing 400044 Peoples R China Hohai Univ Business Sch Nanjing 211100 Peoples R China

As a powerful forward-looking risk management technique, FMEA has been widely used for reliability and security analysis in engineering management fields. In practice, the implementation of FMEA involves the participation of multiple members with distinct knowledge, experience, and cultural background, thus, FMEA is a typical multicriteria group decision-making problem. However, the existence of the aggregation discrepancy issue in FMEA problems with group decision-making leads to collective evaluation conflicts that bring about decision bias for further risk management. This article proposes an AADFMEA method based on multiple-objective optimization to promote the accuracy and reliability of collective assessment information in FMEA members, in which the 10-point qualitative scale is used for evaluation. Additionally, the AADFMEA method responds to the different individual cognitions to a specific evaluation value from multiple members by constraining the risk prioritization to derive more reasonable collective risk evaluation information. Finally, two case studies are presented to show that the AADFMEA method has a good application value, and the simulation analysis was conducted to verify the effectiveness of the proposed AADFMEA approach.

关键词： Frequency modulation Radio frequency Reliability engineering Decision making Aggregates optimization Linguistics Aggregation discrepancy failure mode and effect analysis group decision-making multiple-objective optimization reliability management

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Development of a hybrid CFD-ANN method with multi-objective optimization for airfoil-finned PCHE used in Gen-IV nuclear systems

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PROGRESS IN NUCLEAR ENERGY 2024年 175卷

作者： Ding, Jinneng Liu, Qihang Ke, Juntao Deng, Mingjie Yu, Guopeng Liang, Youcai South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China Shanghai Engn Res Ctr Space Engine Shanghai Inst Space Prop Shanghai 201112 Peoples R China Sun Yat Sen Univ Sino French Inst Nucl Engn & Technol Guangzhou 519082 Guangdong Peoples R China

The airfoil printed circuit heat exchanger (PCHE) is among the most promising exchangers for the supercritical carbon dioxide Brayton cycles in Gen-IV nuclear systems due to its high efficiency and compactness. To optimize the design and analysis of the novel structure, this paper proposes a hybrid CFD-ANN method for the airfoil PCHE with multiple-objective optimization. Firstly, it explores the impact of structural parameters on thermo-hydraulic performance and the synergistic effect of different parameters. It was found that thickness significantly impacts heat exchange and pressure drop, which diminishes when both vertical and horizontal spacing are larger. Smaller horizontal spacing can increase the compactness of the heat exchanger while causing minimal changes in the heat transfer coefficient and pressure drop. Compared to the CFD method, the ANN method can significantly reduce the simulation time from 2 h to 1 s, with a mean absolute percentage error of only 0.61%. In addition, using ANN as the fitness function, and taking the heat transfer coefficient, pressure drop, and compactness as optimization objectives, the results of the optimized design were obtained based on the NSGA-II algorithm. Compared to the original design, the friction factor of optimal design is decreased by 10%, and the compactness increased by 14.8%.

关键词： Airfoil PCHE Hybrid CFD-ANN method multiple-objective optimization Heat transfer and flow correlations

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Life cycle cost and life cycle energy in zero-energy building by multi-objective optimization

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ENERGY REPORTS 2021年 7卷 5612-5626页

作者： She, Chen Jia, Rui Hu, Bei-Ning Zheng, Ze-Kun Xu, Yi-Peng Rodriguez, Dragan TianGong Univ Sch Econ & Management Tianjin 300387 Peoples R China Beijing Jiaotong Univ Sch Econ & Management Dept Construct Management Beijing 100044 Peoples R China Hainan Univ Coll Civil Engn & Architecture Haikou 570100 Hainan Peoples R China Hangzhou HFI Hlth Network Technol Co Ltd Hangzhou Zhejiang Peoples R China Tiangong Univ Sch Math Sci Tianjin 300387 Peoples R China Case Western Reserve Univ Cleveland OH 44106 USA

The energy consumption in buildings is increasing, then, a new global multiple-objective optimization method for zero-energy buildings with the comprehensive assessment method is used in this study. The applied optimization design methods for renewable energy systems are the multiple-objective optimization by Enhanced Archimedes optimization Algorithm (EAOA) on the original design for energy costs and energy optimal models. The Hybrid Gray multiple-Level Comprehensive Assessment Method (HGMLCAM) is utilized to the optimal model including the solar energy use efficacy, energy conservation, economic and social factors. By the selected decision based on the global optimal model, the best solution is presented. For designing the practical building, the defined solution can be useful for the architects and decision-makers. Consequently, a multiple-objective design for a building located in Shanghai, in China, is studied. Based on the results, it can be concluded that the presented method is efficient to make decisions. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： multiple-objective optimization Archimedes optimization algorithm Zero-energy building Solar photovoltaic system Energy-efficiency measures Life cycle energy Life cycle cost

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Classifying the minimum-variance surface of multiple-objective portfolio selection for capital asset pricing models

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ANNALS OF OPERATIONS RESEARCH 2022年第2期311卷 1203-1227页

作者： Qi, Yue China Acad Corp Governance 94 Weijin Rd Tianjin 300071 Peoples R China Nankai Univ Business Sch Dept Financial Management 94 Weijin Rd Tianjin 300071 Peoples R China

Portfolio selection is recognized as the birth-place of modern finance;Markowitz emphasizes computing whole efficient frontiers. Moreover, computing efficient sets has long been a topic in multiple-objective optimization. After portfolio selection, an important research direction is capital asset pricing models (CAPM). Black and Fama prove the existence of a unique zero-covariance portfolio on the minimum-variance frontier. By the zero-covariance relationship, Roll then classifies the minimum-variance frontier into a positive-covariance side and a negative-covariance side;Fama and Roll further prove zero-covariance CAPM. Recently, researchers gradually realize additional criteria and extend portfolio selection into multiple-objective portfolio selection. Consequently, the minimum-variance frontier extends to a minimum-variance surface. Moreover, the extension naturally raises questions of classifying the surface for multiple-objective CAPM. There has been no such research until now. In such an area, this paper contributes to the literature by extending the classification. We classify the surface into a positive-covariance side and a negative-covariance side, although the classification depends on specific portfolios and is thus non-uniform. We then analyze classification properties and extend relevant theorems by proposing conjectures, although the conjectures are disproved by theorems and counter-examples. Moreover, we forward the research methodology to general k-objective models, so research arenas for multiple-objective CAPM are opened. This paper brings researchers one step closer to classifying the minimum-variance surface and extending CAPM.

关键词： multiple-objective optimization multiple-objective portfolio selection Minimum-variance surface Paraboloid Classification Zero-covariance portfolio Capital asset pricing models (CAPM) multiple-objective CAPM

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Rigid-Elastic Combined Metamaterial Beam With Tunable Band Gaps for Broadband Vibration Suppression

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JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME 2024年第2期146卷 021004-021004页

作者： Zhang, Jiazhen Peng, Xuzhang Yu, Dewen Hu, Guobiao Yang, Yaowen Nanyang Technol Univ Sch Civil & Environm Engn Nanyang Ave Singapore 639798 Singapore Hong Kong Univ Sci & Technol Guangzhou Internet Things Thrust Guangzhou 511400 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Key Lab Educ Minist Modern Design & Rotor Bearing Xian 710049 Peoples R China

Extensive research efforts have been dedicated to exploring the application of metamaterial beams for vibration suppression. However, most existing designs primarily focused on utilizing the translational motion of local resonators to create band gaps. To address this limitation of employing solo motion to induce a relatively narrow band gap, this study proposes a novel design: a rigid-elastic combined metamaterial beam utilizing both translational and rotational motions of local resonators. Theoretical framework development involves extending the transfer matrix method to incorporate rigid bodies, with analytical results validated through finite element simulations and experimental data. Compared to conventional metamaterial beams, the proposed design exhibits an additional wide band gap in the low-frequency region that can be utilized for broadband vibration suppression. A parametric study elucidates the influences of geometric parameters on band gap formation, followed by an exploration of the tunability of the proposed meta-beam through a graded scheme and optimization strategy. In particular, a multiple-objective optimization approach is employed to enlarge the vibration suppression region and enhance vibration suppression ability. The optimized meta-beam demonstrates a remarkable 45% wider dominant suppression region and a 14% lower average transmittance compared to a uniform model.

关键词： metamaterial tunable band gap multiple-objective optimization vibration suppression structural dynamics and control vibration control vibration isolation

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Symbolic Encoding of Reliability for the Design of Redundant Architectures 5

Symbolic Encoding of Reliability for the Design of Redundant...

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IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS)

作者： Tierno, Antonio Turri, Giuliano Cimatti, Alessandro Passerone, Roberto Univ Trento Dipartimento Ingn & Sci Informaz Trento Italy Fdn Bruno Kessler Embedded Syst Trento Italy

ISBN: (纸本)9781665497701

In this paper, we propose an approach to automatic optimization of redundant embedded system architectures. Given a high-level description of a system and a library of redundant design patterns, all valid redundant alternative architectures are considered. Then, a model of the deviation of the architecture from its nominal behavior is built, and the set of all fault configurations, also referred to as "cut sets", is computed. This can be used to extract a reliability function for the architecture under study. We leverage the power of Satisfiability Modulo Theory to encode the problem with a symbolic technique, and use the reliability function, together with the assessment of other design objectives, to compare different redundant configurations, thus supporting the exploration of the design space.

关键词： Embedded systems fault-tolerance redundancy allocation reliability analysis design space exploration automatic synthesis multiple-objective optimization

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OPTIMIZING 3-objective PORTFOLIO SELECTION WITH EQUALITY CONSTRAINTS AND ANALYZING THE EFFECT OF VARYING CONSTRAINTS ON THE EFFICIENT SETS

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JOURNAL OF INDUSTRIAL AND MANAGEMENT optimization 2021年第4期17卷 1531-1556页

作者： Qi, Yue Li, Xiaolin Zhang, Su China Acad Corp Governance 94 Weijin Rd Tianjin 300071 Peoples R China Nankai Univ Dept Financial Management Business Sch 94 Weijin Rd Tianjin 300071 Peoples R China

Markowitz proposes portfolio selection as a 2-objective model and emphasizes computing (whole) efficient sets and nondominated sets. Computing the sets has long been a topic in multiple-objective optimization. Researchers have gradually recognized other criteria in addition to variance and expected return. To formulate the additional criteria, researchers propose multiple-objective portfolio selection. However, computing the corresponding efficient set and nondominated set is not fully achieved. Moreover, discovering the sets' properties and utilizing the properties remain typically unanswered. In this paper, we extend Sharpe's and Merton's model by adding a general linear objective and imposing equality constraints. To optimize the model, we analytically derive the minimum-variance surface (defined later), prove it as a nondegenerate paraboloid, and prove the nondominated set as a paraboloidal segment. We also analytically derive the efficient set and prove it as a 2-dimensional translated cone. We then prove that the set subsumes the efficient set of the corresponding traditional model, so the efficient set expands as the general linear objective is added. Furthermore, constraints can be changed or added. We utilize the translated-cone properties and readily compute the changing constraints' effect on the efficient sets by formulae or linear-equation systems.

关键词： multiple-objective optimization multiple-objective portfolio selection efficient set nondominated set paraboloid constraint

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A review on inverse analysis models in steel material design

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Materials Genome Engineering Advances 2024年第4期2卷 26-33页

作者： Yoshitaka Adachi Ta-Te Chen Fei Sun Daichi Maruyama Kengo Sawai Yoshihito Fukatsu Zhi-Lei Wang Nagoya University NagoyaJapanBeijingChina 2JFE Steel CorporationChibaJapanBeijingChina 3University of Science and Technology BeijingBeijingChina

This paper reviews various inverse analysis models used in steel material design,with a focus on integrating process,microstructure,and properties through advanced machine learning *** study underscores the importance of establishing comprehensive models that effectively link these elements for enhanced materials *** models discussed include the convolutional neural network–artificial neural network-coupled model,which employs convolutional neural networks for feature extraction;the Bayesian-optimized generative adversarial network–conditional generative adversarial network model,which generates diverse virtual microstructures;the multi-objective optimization model,which concentrates on process–property relationships;and the microstructure–process parallelization model,which correlates microstructural features with process *** model is assessed for its strengths and limitations,influencing its practical applicability in material *** paper concludes by advocating for continued improvements in model accuracy and versatility,with the ultimate goal of enhancing steel properties and expanding the scope of data-driven material development.

关键词： GAN image regression inverse analysis multiple-objective optimization steel

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A Pareto-discrete hummingbird algorithm for partial sequence-dependent disassembly line balancing problem considering tool requirements

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JOURNAL OF MANUFACTURING SYSTEMS 2021年 60卷 406-428页

作者： Yin, Tao Zhang, Zeqiang Jiang, Jin Southwest Jiaotong Univ Sch Mech Engn Chengdu 610031 Peoples R China Technol & Equipment Rail Transit Operat & Mainten Chengdu 610031 Peoples R China

To reduce the disassembly costs to enterprises and improve the disassembly efficiency of waste products, this study proposed a partial sequence-dependent disassembly line balancing problem (PSD-DLBP) and established a multi-objective mathematical model to simultaneously minimize the number of workstations, total disassembly time, idle balance index and the number of disassembly tools. Then, a Pareto-discrete hummingbird algorithm (PDHA) was proposed to address PSD-DLBP effectively. The PDHA includes two stages: self-searching stage and information-interacting stage. With these two stages, the exploration and exploitation abilities of PDHA can be balanced. Later, the effectiveness and superiority of the PDHA were verified by comparing it with the other four algorithms for two different-scale examples. Finally, the model and PDHA were applied to the optimization of a partial sequence-dependent disassembly line of waste laptops. The optimization results show that the partial disassembly can make the line smoother and the utilization efficiency of workstations higher than full disassembly, and PDHA is superior in solving the PSD-DLBP.

关键词： Sequence-dependent disassembly line Partial disassembly Pareto-discrete hummingbird algorithm Tool requirements multiple-objective optimization

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