Article
Computer Science, Information Systems
Hasitha Muthumala Waidyasooriya, Masanori Hariyama
Summary: Quantum annealing is a method to solve combinatorial optimization problems by utilizing quantum fluctuations, but the processing time increases exponentially with the number of variables. This article introduces a highly-parallel accelerator implemented on FPGA, which achieves significant speed-up compared to single-core CPU implementation.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING
(2021)
Article
Mathematics
Gintaras Palubeckis
Summary: The study proposes a hybrid approach for solving the bidirectional loop layout problem, combining simulated annealing and variable neighborhood search techniques. Experimental results demonstrate the superiority of this hybrid algorithm over standalone simulated annealing and variable neighborhood search. The algorithm also outperformed the current state-of-the-art harmony search heuristic when tested on benchmark tool indexing problem instances.
Review
Computer Science, Theory & Methods
Andre Luis Barroso Almeida, Joubert de Castro Lima, Marco Antonio M. Carvalho
Summary: In the past 35 years, parallel computing has gained increasing interest in the academic community, particularly in addressing complex optimization problems. This survey focuses on the use of high-performance computing techniques to design and implement trajectory-based metaheuristics. It provides a comprehensive overview of the current state-of-the-art in multi-core and distributed trajectory-based metaheuristics, introducing basic concepts of high-performance computing and reviewing different taxonomies for architectures and metaheuristics. The survey also presents a summary and classification of 127 publications, identifies research gaps, and discusses past and future trends.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Artificial Intelligence
Wenna Wang, Xiuwei Zhang, Hengfei Cui, Hanlin Yin, Yannnig Zhang
Summary: The paper proposes an efficient search method, FP-DARTS, which is carefully designed to construct and train a super-network from three levels. Different strategies are adopted to reduce computational burden and improve efficiency. extensive experiments demonstrate the effectiveness of the proposed algorithm.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Artificial Intelligence
Narcis Coll, Marta Fort, Moises Saus
Summary: This study presents a system for determining the optimal locations for k disk-like services to maximize the coverage of a demand region. The study focuses on the facility location field and addresses the challenge of locating multiple services efficiently. The proposed system utilizes a parallel simulated annealing optimization technique to provide good enough solutions within reasonable running times.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Esra Celik, Deniz Dal
Summary: This study introduces a simulated annealing-based metaheuristic for cluster-based task scheduling, implemented in both serial and parallel versions in C++. The effectiveness of the method is demonstrated through twelve benchmarks from the Braun dataset, with both versions outperforming the best latency values reported in the literature within 90 seconds. Various techniques and considerations, such as random number generation, data structures, and compiler effects, are analyzed to improve the quality of scheduling solutions and decrease program execution time.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Automation & Control Systems
Kun Shi, Zhengtian Wu, Baoping Jiang, Hamid Reza Karimi
Summary: Dynamic path planning for mobile robots is crucial due to their increasing usage. This study introduces an improved simulated annealing algorithm for avoiding moving obstacles in dynamic situations. The algorithm reduces computational effort through initial path selection and deletion operations. Simulation results demonstrate the algorithm's superiority over others in both static and dynamic environments.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Kaipu Wang, Xinyu Li, Liang Gao, Peigen Li, Surendra M. Gupta
Summary: In this paper, a parallel partial disassembly line balancing model is established, and a new genetic simulated annealing algorithm is proposed to optimize the model, which can improve the disassembly efficiency and economic benefits. The proposed algorithm shows superior performance in practical applications.
APPLIED SOFT COMPUTING
(2021)
Article
Mathematics
Ibrahim Attiya, Laith Abualigah, Samah Alshathri, Doaa Elsadek, Mohamed Abd Elaziz
Summary: This paper presents a novel dynamic Jellyfish Search Algorithm using a Simulated Annealing and disruption operator, called DJSD, which effectively improves the search performance and addresses the issue of local optima. Experimental results show that the proposed method achieves promising results in various benchmark functions and real-world applications.
Article
Computer Science, Artificial Intelligence
Juan Lin, Ailing Shen, Liangcheng Wu, Yiwen Zhong
Summary: This paper proposes a learning-based simulated annealing algorithm to tackle the NP-hard unequal area facility layout problem. The algorithm incorporates a novel solution representation, an improved penalty function, and a diverse set of neighborhood operators to refine the search space. By utilizing a reinforcement learning-based controller, the algorithm enables a flexible and efficient exploration, further exploiting the search space and enhancing solution quality.
Article
Engineering, Civil
Jiqiang Li, Guoqing Zhang, Xianku Zhang, Weidong Zhang
Summary: This paper presents a robust adaptive event-triggered control strategy for the cooperative system of underactuated surface vessel-unmanned aerial vehicles (USV-UAVs) to perform maritime parallel search missions. The proposed scheme consists of a three-dimensional search guidance principle and a cooperative formation control law. By considering the maneuvering characteristics of the heterogeneous agents, the developed guidance principle generates reference signals for the USV and UAVs at waypoints. The control algorithm, which combines dynamic event-triggered mechanism and sensor-tolerant technique, ensures stable and tolerant performance.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Heng Ding, Yude Dong, Haoyu Gao, Hui Cheng, Zhongshu Yang, Yulei Liang
Summary: The problem of workpiece position error caused by fixture source error is solved by an improved simulated annealing algorithm and a point differentiation method, resulting in a more robust workpiece positioning method.
ADVANCED THEORY AND SIMULATIONS
(2023)
Article
Agricultural Engineering
Jianfeng Zou, Hangli Hu, Md Maksudur Rahman, Dominic Yellezuome, Fang He, Xingguang Zhang, Junmeng Cai
Summary: Biomass pyrolysis is an important method for converting biomass into fuels and chemicals for sustainability and carbon neutralization. This study proposed a hybrid optimization method to accurately determine the parameters of the distributed activation energy model and successfully reproduced experimental data.
INDUSTRIAL CROPS AND PRODUCTS
(2022)
Article
Environmental Sciences
Anh Vu Vo, Debra E. Laefer, Jonathan Byrne
Summary: This paper introduces an approach utilizing genetic algorithm and beam tracing algorithm to optimize urban aerial laser scanning tasks. The method aims to maximize vertical data capture through a low-density point cloud representation of the urban scene, and achieves fast and scalable results with a dual parallel computing framework and two layers of parallelization.
Article
Automation & Control Systems
Ricardo Martins, Nuno Lourenco, Ricardo Povoa, Nuno Horta
Summary: This paper proposes an automatic device placement methodology that explicitly accounts for and minimizes layout-dependent effects, aiming to shorten the gap between preand post-layout performance by reducing the variations induced by LDEs.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Environmental Sciences
Subhash Paul, Animesh Dutta, Fantahun Defersha, Brajesh Dubey
WASTE AND BIOMASS VALORIZATION
(2018)
Article
Automation & Control Systems
Wisam Al-Wajidi, Ibrahim Deiab, Fantahun M. Defersha, Abdallah Elsayed
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2019)
Review
Green & Sustainable Science & Technology
Poritosh Roy, Debela Tadele, Fantahun Defersha, Manjusri Misra, Amar K. Mohanty
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2019)
Article
Green & Sustainable Science & Technology
Debela Tadele, Poritosh Roy, Fantahun Defersha, Manjusri Misra, Amar K. Mohanty
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2020)
Article
Polymer Science
Alison Gowman, Arturo Rodriguez-Uribe, Fantahun Defersha, Amar K. Mohanty, Manjusri Misra
JOURNAL OF APPLIED POLYMER SCIENCE
(2020)
Article
Computer Science, Interdisciplinary Applications
Fantahun M. Defersha, Danial Rooyani
COMPUTERS & INDUSTRIAL ENGINEERING
(2020)
Article
Polymer Science
Ahmed Z. Naser, Ibrahim Deiab, Fantahun Defersha, Sheng Yang
Summary: Due to the high price of petroleum, overconsumption of plastic products, recent climate change regulations, lack of landfill spaces, and increasing population, sustainable biodegradable solutions are being introduced for a greener environment. Biodegradable biobased polymers such as PLA and PHAs have gained attention as environmentally friendly alternatives to petroleum-based plastics, despite limitations in flexibility and impact resistance. Advances in modification methods show potential for overcoming these limitations, expanding the applications of both polymers in various fields such as food packaging, surgical implants, and biomedical applications.
Article
Chemistry, Multidisciplinary
Syeda M. Tahsien, Fantahun M. Defersha
Summary: This paper presents a technique for converting ordered permutations to binary vectors, and applies it to clustering and discriminating the permutations. The study shows that the Improved ART-1 neural network performs better than ART-1, and a neural network-guided Genetic Algorithm outperforms a pure Genetic Algorithm.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Danial Rooyani, Fantahun Defersha
Summary: This paper extends the application of a two-stage genetic algorithm from a comprehensive model of flexible job-shop scheduling problem (FJSP) to solve a lot streaming problem in FJSP with multiple objectives. Numerical examples are used to demonstrate the need for multi-objective optimization, the interaction between different objective functions, and the better solution quality provided by the algorithm. The results show that the two-stage genetic algorithm outperforms the regular genetic algorithm in convergence speed and final solution quality for the multi-objective FJSP lot streaming.
Article
Computer Science, Interdisciplinary Applications
Fantahun M. Defersha, Dolapo Obimuyiwa, Alebachew D. Yimer
Summary: In most published articles on flexible job shop scheduling problems (FJSP), the focus is primarily on the limited capacities of machines as the constraining resources. However, with the increasing adoption of numerically controlled machines with self-controlling capabilities, the role of machine operators has changed from performing sequential steps to becoming machine tenders. This paper proposes a mathematical model for a new setup operator constrained FJSP (SOC-FJSP), where setup operations are assumed to be detached. The proposed simulated annealing algorithm is developed to solve the mathematical model, and further extensions are made to account for sequence-dependent setup time and workload balancing among the setup operators.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Poritosh Roy, Fantahun Defersha, Arturo Rodriguez-Uribe, Manjusri Misra, Amar K. Mohanty
JOURNAL OF CLEANER PRODUCTION
(2020)
Proceedings Paper
Automation & Control Systems
Mohammad M. Jalalian, Fantahun M. Defersha
Proceedings Paper
Automation & Control Systems
Danial Rooyani, Fantahun M. Defersha
Article
Energy & Fuels
Debela Tadele, Poritosh Roy, Fantahun Defersha, Manjusri Misra, Amar K. Mohanty
Article
Thermodynamics
Subhash Paul, Animesh Dutta, Mahendra Thimmanagari, Fantahun Defersha
CASE STUDIES IN THERMAL ENGINEERING
(2019)
Article
Engineering, Industrial
Xiaoliang Yan, Reed Williams, Elena Arvanitis, Shreyes Melkote
Summary: This paper extends prior work by developing a semantic segmentation approach for machinable volume decomposition using pre-trained generative process capability models, providing manufacturability feedback and labels of candidate machining operations for query 3D parts.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
