Article
Geochemistry & Geophysics
Xiaohua Xu, Zhanghai Ju, Jia Luo
Summary: In this simulation study, operational GNSS satellites are used for global navigation satellite system reflectometry (GNSS-R) measurement. Different constellations of satellites are designed and optimized using multiobjective evolutionary algorithms. The optimal constellations show similar performance in terms of coverage and revisited coverage with specific inclinations and orbital altitudes.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Automation & Control Systems
Kai Zhang, Gary G. Yen, Zhenan He
Summary: In this article, a recursive evolutionary algorithm EvoKnee(R) is proposed to directly search for global knee solutions and multiple local knee solutions using the minimum Manhattan distance approach, instead of a large number of Pareto optimal solutions. Unlike traditional approaches, only nondominated solutions in rank one are preserved in each generation, reducing computational cost and allowing quick convergence to knee solutions.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Gaurav Srivastava, Alok Singh, Rammohan Mallipeddi
Summary: This paper proposes a nondominated sorting genetic algorithm II approach to address the vehicle routing problem with time windows, known for its multiobjective characteristics. The performance of this approach is evaluated on standard benchmark instances, showing its superiority over the state-of-the-art approach for the problem.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Chen Xing, Kang Li, Li Zhang, Zhongbei Tian
Summary: Railway electrification is an important aspect of global transport decarbonization efforts. This article proposes a biobjective robust optimization model to minimize energy consumption and journey time in train operations, considering uncertain train mass associated with passenger load variations. A novel multiobjective optimization algorithm, p-nondominated sorting genetic algorithm-II (NSGA-II), is proposed to handle decision-makers' preferences and improve robustness. Numerical case studies confirm the effectiveness of the proposed algorithm, with up to 40.59% improvement in robustness compared to the original NSGA-II.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Automation & Control Systems
Javier Moreno, Daniel Rodriguez, Antonio J. Nebro, Jose A. Lozano
Summary: This article introduces a new efficient algorithm MNDS for computing the nondominated sorting procedure, which outperforms other techniques in terms of computational complexity and running time. The algorithm is based on the computation of the dominance set and takes advantage of the characteristics of the merge sort algorithm.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Geochemistry & Geophysics
Chuanlong Ye, Fazhi He, Jinkun Luo, Lyuyang Tong, Xiaoxin Gao, Tongzhen Si, Linkun Fan
Summary: This article proposes a multistrategy evolutionary multiobjective method based on roulette wheel selection and the genetic algorithm (RWS-GA) for hyperspectral endmember extraction. The method designs two parallel algorithms corresponding to global exploration and local exploitation. Experimental results show that the proposed method outperforms other endmember extraction methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Review
Computer Science, Interdisciplinary Applications
Reza Behmanesh, Iman Rahimi, Amir H. Gandomi
Summary: This study tested 18 evolutionary many-objective algorithms on various combinatorial optimization problems, showing that different types of algorithms have different performances in solving different problems.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Shufen Qin, Chaoli Sun, Yaochu Jin, Ying Tan, Jonathan Fieldsend
Summary: This article proposes a large-scale multiobjective evolutionary algorithm assisted by directed sampling, which selects individuals closer to the ideal point for reproduction to improve convergence. It also adopts elitist nondominated sorting and a reference vector-based method for environmental selection in order to maintain population diversity. Experimental results demonstrate the competitiveness of the proposed algorithm on large-scale multiobjective optimization problems.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2021)
Article
Multidisciplinary Sciences
Saykat Dutta, Rammohan Mallipeddi, Kedar Nath Das
Summary: In this work, a Hybrid Selection based MOEA (HS-MOEA) is proposed, which effectively balances the diversity and convergence properties of MOEA by combining Pareto-dominance, reference vectors, and an indicator. Experimental simulations on DTLZ and WFG test suites demonstrate the superior performance of HS-MOEA compared to state-of-the-art MOEAs, with up to 10 objectives.
SCIENTIFIC REPORTS
(2022)
Article
Nuclear Science & Technology
Orestes Castillo-Hernandez, P. E. Manuel Perdomo-Ojeda, C. R. Grantom, Pamela F. Nelson
Summary: Incorporating specified safety and production targets during the design phase can reduce costs and enhance the competitiveness of nuclear power plants. This paper presents two methods for proposing unavailability targets for nuclear reactor systems to optimize the design features. The methods are applied to a hypothetical facility, providing a basis for future work on estimating design alternatives affecting unavailabilities.
NUCLEAR ENGINEERING AND DESIGN
(2024)
Article
Computer Science, Artificial Intelligence
Peidi Wang, Yongjie Ma
Summary: The DMOEA is a powerful solver for DMOPs, but the current algorithms lack strategies in both the environment response and static optimization stages. To address this, a new algorithm was proposed that incorporates different strategies in both stages to balance convergence and diversity. The algorithm uses nondominated solutions-guided evolution in the static optimization stage and fine prediction strategy in the environment response stage to improve performance in dynamic environments.
APPLIED INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Guifu Du, Chengqian Zhu, Xingxing Jiang, Qiaoyue Li, Weiguo Huang, Jie Shi, Zhongkui Zhu
Summary: This article discusses frequent power supply accidents and excessive energy consumption in dc traction power systems (dc TPSs) of multitrain subway lines. A multiobjective optimization approach is proposed to optimize the traction substation (TSS) converter characteristic and train timetable for safe and economic operation of subway systems. The results show significant reductions in the optimized objectives, namely rail potential (RP), energy consumption, and maximum traction current, indicating improved energy conservation and power supply safety in subway systems.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Computer Science, Artificial Intelligence
Pengbo Wang, Houxiu Xiao, Xiaotao Han, Fan Yang, Liang Li
Summary: This paper proposes an archive-assisted evolutionary framework to address the challenges faced by evolutionary algorithms in constrained multiobjective optimization problems. The framework uses a reference line guided archive, an adaptive mating selection operator, and skipping infeasible regions for extensive searches to improve the feasibility, convergence, and diversity of the algorithms.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
S. Mohan, Akash Sinha
Summary: This paper proposes a novel method for performing nondominated sorting in a multiobjective optimization problem using a modified directional Bat algorithm. Unlike NSGA-II, the proposed algorithm generates and compares new solutions with all previous solutions, reducing computational time and generating diverse solutions. A unique sorting method using a Nondomination matrix is introduced, which can be easily updated to include new solutions and preserve elitism. Detailed criteria are provided for the selection of new solutions. Experimental results show that the proposed algorithm is competitive and outperforms other algorithms in terms of efficiency and other performance metrics for most benchmark optimization problems. The algorithm also provides a standardized platform for nondomination sorting, applicable to any other metaheuristic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Marine
Yuchuang Wang, Guoyou Shi, Katsutoshi Hirayama
Summary: This article proposes a many-objective solution for the container ship stowage planning problem, which takes into account factors such as ship stability, number of shifts, and realistic constraints. The variant of the nondominated sorting genetic algorithm III is used to solve the problem effectively.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Environmental Sciences
Peng Wang, Aaron C. Zecchin, Holger R. Maier, Feifei Zheng, Jeffrey P. Newman
WATER RESOURCES RESEARCH
(2020)
Article
Geosciences, Multidisciplinary
Graeme A. Riddell, Hedwig van Delden, Holger R. Maier, Aaron C. Zecchin
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2020)
Review
Water Resources
Wenyan Wu, Holger R. Maier, Graeme C. Dandy, Meenakshi Arora, Andrea Castelletti
JOURNAL OF WATER AND CLIMATE CHANGE
(2020)
Article
Environmental Sciences
C. McPhail, H. R. Maier, S. Westra, J. H. Kwakkel, L. van der Linden
WATER RESOURCES RESEARCH
(2020)
Article
Computer Science, Interdisciplinary Applications
Charles P. Newland, Hedwig van Delden, Aaron C. Zecchin, Jeffrey P. Newman, Holger R. Maier
ENVIRONMENTAL MODELLING & SOFTWARE
(2020)
Article
Computer Science, Interdisciplinary Applications
S. Culley, H. R. Maier, S. Westra, B. Bennett
Summary: The use of scenario-neutral climate impact assessments is increasing to evaluate water resource system responses to climate changes. These assessments aim to identify system sensitivity to different climate conditions and stressors, with results showing that the choice of climate conditions included can significantly impact the assessment outcome.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Computer Science, Interdisciplinary Applications
Saman Razavi, Anthony Jakeman, Andrea Saltelli, Clementine Prieur, Bertrand Iooss, Emanuele Borgonovo, Elmar Plischke, Samuele Lo Piano, Takuya Iwanaga, William Becker, Stefano Tarantola, Joseph H. A. Guillaume, John Jakeman, Hoshin Gupta, Nicola Melillo, Giovanni Rabitti, Vincent Chabridon, Qingyun Duan, Xifu Sun, Stefan Smith, Razi Sheikholeslami, Nasim Hosseini, Masoud Asadzadeh, Arnald Puy, Sergei Kucherenko, Holger R. Maier
Summary: Sensitivity analysis is becoming an essential part of mathematical modeling, with untapped potential benefits for both mechanistic and data-driven modeling as well as decision making. This perspective paper revisits the current status of SA and outlines research challenges in various areas, emphasizing the need for structuring and standardizing SA as a discipline, tapping into its potential for systems modeling, addressing computational burdens, progressing SA in the context of machine learning, clarifying its relationship with uncertainty quantification, and evolving its use in decision making. An outlook for the future of SA is provided to better serve science and society.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Computer Science, Interdisciplinary Applications
Bree Bennett, Anjana Devanand, Sam Culley, Seth Westra, Danlu Guo, Holger R. Maier
Summary: The article introduces a unified five-step framework and supporting R-package, foreSIGHT, for conducting climate impact assessments in a scenario-neutral manner. The software enables the analysis of system performance, comparing current performance with alternative management or design options, and includes a case study demonstration.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Article
Computer Science, Interdisciplinary Applications
C. McPhail, H. R. Maier, S. Westra, L. van der Linden, J. H. Kwakkel
Summary: In order to assist decision making about environmental systems under deep uncertainty, researchers have introduced a generic guidance framework and software package to help identify the most robust decision alternatives. This tackles the difficulty of choosing between robustness metrics and scenarios, providing a consistent and easy-to-use approach to quantify system robustness and make robust decisions.
ENVIRONMENTAL MODELLING & SOFTWARE
(2021)
Review
Engineering, Environmental
Yueyi Jia, Feifei Zheng, Holger R. Maier, Avi Ostfeld, Enrico Creaco, Dragan Savic, Jeroen Langeveld, Zoran Kapelan
Summary: Water quality models are a promising way to address water quality issues in urban sewer networks. Currently, there is a trend towards using empirical and kinetic models for prediction and process understanding, but the accuracy of the models needs improvement. Future research directions include determining appropriate data resolutions for different SN models, developing hybrid SN models, and enhancing SN model transferability.
Article
Computer Science, Interdisciplinary Applications
S. Zhu, H. R. Maier, A. C. Zecchin
Summary: This paper investigates optimization methods for environmental problems and proposes 28 efficient feature metrics that can be applied to real-world problems to better understand their characteristics and determine the most suitable optimization algorithms.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Civil
Ruijie Liang, Mark A. Thyer, Holger R. Maier, Graeme C. Dandy, Michael Di Matteo
Summary: This study introduces a two-step method to minimize peak flows by optimizing the layout of distributed storages and their RTC strategies, showing that optimized layouts can achieve higher peak flow reductions than traditional end-of-system storage. The addition of optimized RTC can further reduce peak flows, with more significant effects on smaller storage volumes. Analysis of flood hydrographs indicates that peak flow reductions are achieved through attenuation at individual storages and delaying hydrographs to reduce coincidence at catchment confluences.
JOURNAL OF HYDROLOGY
(2021)
Article
Construction & Building Technology
Douglas A. G. Radford, Thomas C. Lawler, Brandon R. Edwards, Benjamin R. W. Disher, Holger R. Maier, Bertram Ostendorf, John Nairn, Hedwig van Delden, Michael Goodsite
Summary: This study introduces a generic framework for quantifying and evaluating heat-related risks to infrastructure assets and explores mitigation strategies. Applied to a case study in Adelaide, Australia, the results demonstrate the value of this framework in managing heat-sensitive infrastructure assets.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Engineering, Civil
A. C. Zecchin, N. Do, J. Gong, M. Leonard, M. F. Lambert, M. L. Stephens
Summary: This paper investigates the criteria for optimal sensor deployment in a water distribution system and develops a technique for determining the optimal sensor locations. By maximizing the network extent for detecting and locating hydraulic transient events, the concept of event locatability is proposed. The effectiveness of the proposed method is verified through case studies.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Peng Wang, Aaron C. C. Zecchin, Holger R. R. Maier
Summary: Multi-objective evolutionary algorithms (MOEAs) have been widely used for water distribution system (WDS) optimization problems for more than 20 years. This paper proposes a novel selection strategy called convex hull contribution (CHC) selection strategy for generational MOEAs (CHCGen), which outperforms existing popular selection strategies and improves the performance of existing MOEAs such as NSGA-II and GALAXY. The effectiveness of the CHCGen strategy is demonstrated through numerical experiments on six bi-objective WDS problems.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)