Article
Engineering, Mechanical
Dominik Vondracek, Zdenek Padovec, Tomas Mares, Nirupam Chakraborti
Summary: The strength analyses of the junction between cylindrical part and different types of known end domes for filament wound composite pressure vessels were performed. The study also deals with the design of an optimal end dome shape that takes into account the junction area. The results indicate a strong dependence of the optimal end dome shape on material properties.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Hui Zhang, Xiaojuan Zheng
Summary: This paper proposes a knowledge-driven adaptive evolutionary multi-objective scheduling algorithm (KAMSA) for optimizing makespan and cost of workflow execution in cloud platforms. It divides large-scale decision variables into groups using divide-and-conquer technology to improve evolutionary search efficiency. Comparison with five state-of-the-art competitors demonstrates KAMSA's advantages in 18 out of 20 test cases.
APPLIED SOFT COMPUTING
(2023)
Article
Mechanics
Kaite Guo, Shuai Chen, Lihua Wen, Jinyou Xiao
Summary: A novel method is proposed to predict the thickness of composite vessels without relying on the straight-line assumption. The winding pattern obtained from the non-geodesic equations is considered in this method. A model is developed to determine the critical band width for full fiber coverage, and the geodesic offset is used to calculate the band boundary lines. The effectiveness of the method is validated by comparing the predicted thickness with experimental results, showing a high precision with an average relative error of 1.51%. The influence of the winding pattern on the thickness distribution is demonstrated by calculating the dome thickness for a specific composite pressure vessel and comparing it with other methods. It is found that the circuit number decreases and the thickness decreases with an increase in the dome slippage coefficient.
COMPOSITE STRUCTURES
(2023)
Article
Computer Science, Artificial Intelligence
Lei Zhang, Haipeng Yang, Shangshang Yang, Xingyi Zhang
Summary: This study proposes a macro-micro population-based co-evolutionary multi-objective algorithm called MMCoMO for community detection in complex networks. The algorithm employs two populations, macro-population and micro-population, to obtain better community structures.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Computer Science, Theory & Methods
Soheila Sadeghiram, Hui Ma, Gang Chen
Summary: Service-oriented architecture (SOA) promotes the use of Web services as reusable components in modular applications. Data-intensive Web services manipulate and handle large volumes of data. Distributed Data-intensive Web Service Composition (DWSC) involves selecting and combining data-intensive Web services from different locations to achieve complex tasks. This paper proposes an Evolutionary Computation (EC) approach based on Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel local search technique to effectively solve the multi-objective distributed DWSC problems. The proposed approach demonstrates superior performance in terms of quality and execution time compared to competing algorithms.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Zhenyu Lei, Shangce Gao, Zhiming Zhang, MengChu Zhou, Jiujun Cheng
Summary: Protein structure prediction is a significant biocomputing challenge, and a complete solution using computational methods has not yet been achieved. This study proposes a many-objective approach to improve the accuracy of predicting protein structures by utilizing evolutionary algorithms. Experimental results show that this method can yield more accurate and efficient protein structure predictions.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Computer Science, Artificial Intelligence
Yiping Liu, Xinyi Zhang, Yuansheng Liu, Yansen Su, Xiangxiang Zeng, Gary G. Yen
Summary: This paper presents an evolutionary multi-objective approach for designing antimicrobial peptides (AMPs) that optimizes both antimicrobial activity and diversity. The approach utilizes a deep learning model to predict antimicrobial activity and a niche sharing method to estimate peptide density. An evolutionary multi-objective algorithm is used to simultaneously optimize antimicrobial activity and diversity, and a local search strategy is applied to improve the quality of the identified AMPs. Experimental results demonstrate the superiority of the proposed approach in searching for diverse AMPs with high antimicrobial activities.
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE
(2023)
Article
Engineering, Multidisciplinary
Lei Zhang, Bin Li, Haipeng Yang, Fan Cheng, Cheng Zhang, Renzhi Cao
Summary: In this paper, a novel multi-objective model and a tri-division representation-based multi-objective evolutionary algorithm (TDR-MOEA) are proposed for local overlapping community detection. The effectiveness of the proposed approach is verified through experiments on both synthetic and real-world networks.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Elaine Guerrero-Pena, Aluizio F. R. Araujo
Summary: Dynamic multi-objective evolutionary algorithms can address multi-objective optimization problems by predicting and responding to changes, with prediction-based methods showing promise. Through the use of objective space prediction strategy and change reaction mechanism, the proposed DOSP-NSDE demonstrates competitiveness in experiments.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Artificial Intelligence
Qiqi Liu, Yuping Yan, Peter Ligeti, Yaochu Jin
Summary: This article proposes a secure federated data-driven evolutionary multi-objective optimization algorithm that protects both raw data and newly infilled solutions. The algorithm selects query points on randomly selected clients and masks objective values to enhance privacy and security.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2023)
Article
Computer Science, Theory & Methods
Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng He, Kay Chen Tan, Yaochu Jin
Summary: This article provides a comprehensive survey of state-of-the-art MOEAs for solving large-scale multi-objective optimization problems, categorizing them into different types and discussing their strengths and weaknesses. It also reviews benchmark problems for performance assessment and important applications, while also addressing remaining challenges and future research directions in evolutionary large-scale multi-objective optimization.
ACM COMPUTING SURVEYS
(2021)
Article
Computer Science, Artificial Intelligence
Yinan Shao, Jerry Chun-Wei Lin, Gautam Srivastava, Dongdong Guo, Hongchun Zhang, Hu Yi, Alireza Jolfaei
Summary: This article introduces a method for optimizing deep reinforcement learning models using neural evolutionary algorithms to solve combinatorial optimization problems. The proposed end-to-end multi-objective neural evolutionary algorithm demonstrates competitive and robust performance on the classic travel salesman problem and knapsack problem, and also performs well in inference time.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Derya Deliktas, Ender Ozcan, Ozden Ustun, Orhan Torkul
Summary: The study introduces evolutionary algorithms to solve the bi-objective flexible job shop scheduling problem and compares their performance across various configurations. The transgenerational memetic algorithm using weighted sum method outperforms others and achieves the best-known results for almost all instances of bi-objective flexible job shop cell scheduling.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Giovanni Acampora, Autilia Vitiello
Summary: This study introduces a new evolutionary algorithm utilizing an actual quantum processor, which employs quantum phenomena to achieve significant speed-up in computation. By implementing quantum concepts such as quantum chromosome and entangled crossover, the proposed algorithm efficiently executes genetic evolution on quantum devices to converge towards proper sub-optimal solutions of a given optimization problem. The experimental results show that the synergy between quantum and evolutionary computation leads to a promising bio-inspired optimization strategy.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Fernando Jimenez, Estrella Lucena-Sanchez, Gracia Sanchez, Guido Sciavicco
Summary: This paper introduces a comprehensive optimization model for detecting the causes of contamination in underground water wells, addressing the issues of selecting the best predicting variables and detecting outliers simultaneously. The results demonstrate that the proposed model can generate reliable, interpretable, and clean regression models.
Article
Polymer Science
Ivan Kelnar, Ludmila Kapralkova, Jaroslav Kratochvil, Zdenek Padovec, Milan Ruzicka, Jirina Hromadkova
Article
Polymer Science
Ivan Kelnar, Jaroslav Kratochvil, Ludmila Kapralkova, Alexander Zhigunov, Zdenek Padovec, Milan Ruzicka, Martina Nevoralova
JOURNAL OF APPLIED POLYMER SCIENCE
(2017)
Article
Mechanics
Z. Padovec, M. Ruzicka, R. Sedlacek, M. Kral, P. Ruzicka
MECHANICS OF COMPOSITE MATERIALS
(2017)
Article
Materials Science, Characterization & Testing
Ivan Kelnar, Aleksandra Ujcic, Ludmila Kapralkova, Sabina Krejcikova, Alexander Zhigunov, Ctirad Novotny, Zdenek Padovec, Milan Ruzicka
Article
Mechanics
Z. Padovec, J. Krena, R. Sedlacek, T. Zamecnikova
Summary: The study describes the design, finite-element analysis, and testing of two optimized composite profiles used for joining aircraft structures. Profiles with T and Y shapes were manufactured using thermoforming technology by a one-shot process. Both static and fatigue tests confirmed that the profiles could withstand the prescribed load without degradation, consistent with FE simulations.
MECHANICS OF COMPOSITE MATERIALS
(2022)
Article
Materials Science, Multidisciplinary
Ivan Kelnar, Ludmila Kapralkova, Pavel Nemecek, Miroslav Janata, Jiri Dybal, Jan Svoboda, Zdenek Padovec, A. M. Abdel-Mohsen
Summary: This study introduces a new concept to improve the limited delamination resistance of high-performance fibrous composites by forming a nanostructured ordered rigid tough interface with controllable thickness and parameters, thereby increasing impact energy release and resistance to delamination.
MATERIALS TODAY COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Anna Mala, Zdenek Padovec, Tomas Mares, Nirupam Chakraborti
Summary: This study applied an optimization methodology to composite frame structures and achieved desirable parameters through adjustments in winding angles and tube ply thicknesses. The findings highlight the effectiveness and transferability of the optimization approach across different geometries.
PHILOSOPHICAL MAGAZINE LETTERS
(2023)
Article
Engineering, Mechanical
Dominik Vondracek, Zdenek Padovec, Tomas Mares, Nirupam Chakraborti
Summary: The strength analyses of the junction between cylindrical part and different types of known end domes for filament wound composite pressure vessels were performed. The study also deals with the design of an optimal end dome shape that takes into account the junction area. The results indicate a strong dependence of the optimal end dome shape on material properties.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
(2023)
Proceedings Paper
Engineering, Multidisciplinary
L. Kazda, M. Ruzicka, Z. Padovec, G. Achtenova, R. Poul
ENGINEERING MECHANICS 2020 (IM2020)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Radek Sedlacek, Tomas Suchy, Zdenek Padovec
XV MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING - MEDICON 2019
(2020)
Proceedings Paper
Engineering, Mechanical
Zdenek Padovec, Radek Sedlacek, Tereza Zamecnikova
EXPERIMENTAL STRESS ANALYSIS (EAN 2019)
(2019)
Proceedings Paper
Engineering, Mechanical
Radek Sedlacek, Tomas Suchy, Zdenek Padovec
EXPERIMENTAL STRESS ANALYSIS (EAN 2019)
(2019)
Proceedings Paper
Materials Science, Multidisciplinary
Zdenek Padovec, Hynek Chlup, Radek Sedlacek, Michal Kral, Milan Ruzicka, Pavel Ruzicka
MATERIALS TODAY-PROCEEDINGS
(2016)
