Quantum-Inspired Distributed Memetic Algorithm
This paper proposed a novel distributed memetic evolutionary model, where four modules distributed exploration, intensified exploitation, knowledge transfer, and evolutionary restart are coevolved to maximize their strengths and achieve superior global optimality. Distributed exploration evolves thr...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2022-12-01
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| Series: | Complex System Modeling and Simulation |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.23919/CSMS.2022.0021 |
| _version_ | 1827090917716131840 |
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| author | Guanghui Zhang Wenjing Ma Keyi Xing Lining Xing Kesheng Wang |
| author_facet | Guanghui Zhang Wenjing Ma Keyi Xing Lining Xing Kesheng Wang |
| author_sort | Guanghui Zhang |
| collection | DOAJ |
| description | This paper proposed a novel distributed memetic evolutionary model, where four modules distributed exploration, intensified exploitation, knowledge transfer, and evolutionary restart are coevolved to maximize their strengths and achieve superior global optimality. Distributed exploration evolves three independent populations by heterogenous operators. Intensified exploitation evolves an external elite archive in parallel with exploration to balance global and local searches. Knowledge transfer is based on a point-ring communication topology to share successful experiences among distinct search agents. Evolutionary restart adopts an adaptive perturbation strategy to control search diversity reasonably. Quantum computation is a newly emerging technique, which has powerful computing power and parallelized ability. Therefore, this paper further fuses quantum mechanisms into the proposed evolutionary model to build a new evolutionary algorithm, referred to as quantum-inspired distributed memetic algorithm (QDMA). In QDMA, individuals are represented by the quantum characteristics and evolved by the quantum-inspired evolutionary optimizers in the quantum hyperspace. The QDMA integrates the superiorities of distributed, memetic, and quantum evolution. Computational experiments are carried out to evaluate the superior performance of QDMA. The results demonstrate the effectiveness of special designs and show that QDMA has greater superiority compared to the compared state-of-the-art algorithms based on Wilcoxon’s rank-sum test. The superiority is attributed not only to good cooperative coevolution of distributed memetic evolutionary model, but also to superior designs of each special component. |
| first_indexed | 2024-04-10T22:42:46Z |
| format | Article |
| id | doaj.art-a6f8be9bc92646b6be8fbd8f21e2ac8e |
| institution | Directory Open Access Journal |
| issn | 2096-9929 |
| language | English |
| last_indexed | 2025-03-20T05:48:01Z |
| publishDate | 2022-12-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Complex System Modeling and Simulation |
| spelling | doaj.art-a6f8be9bc92646b6be8fbd8f21e2ac8e2024-10-03T03:53:30ZengTsinghua University PressComplex System Modeling and Simulation2096-99292022-12-012433435310.23919/CSMS.2022.0021Quantum-Inspired Distributed Memetic AlgorithmGuanghui Zhang0Wenjing Ma1Keyi Xing2Lining Xing3Kesheng Wang4School of Information Science and Technology and the Hebei Key Laboratory of Agricultural Big Data, Hebei Agricultural University, Baoding 071001, ChinaSchool of Information Science and Technology, Hebei Agricultural University, Baoding 071001, ChinaState Key Laboratory for Manufacturing System Engineering and the Systems Engineering Institute, Xi’an Jiaotong University, Xi’an 710049, ChinaSchool of Electronic, Xidian University, Xi’an 710071, ChinaDepartment of Production and Quality Engineering, Norwegian University of Science and Technology, Trondheim 7491, NorwayThis paper proposed a novel distributed memetic evolutionary model, where four modules distributed exploration, intensified exploitation, knowledge transfer, and evolutionary restart are coevolved to maximize their strengths and achieve superior global optimality. Distributed exploration evolves three independent populations by heterogenous operators. Intensified exploitation evolves an external elite archive in parallel with exploration to balance global and local searches. Knowledge transfer is based on a point-ring communication topology to share successful experiences among distinct search agents. Evolutionary restart adopts an adaptive perturbation strategy to control search diversity reasonably. Quantum computation is a newly emerging technique, which has powerful computing power and parallelized ability. Therefore, this paper further fuses quantum mechanisms into the proposed evolutionary model to build a new evolutionary algorithm, referred to as quantum-inspired distributed memetic algorithm (QDMA). In QDMA, individuals are represented by the quantum characteristics and evolved by the quantum-inspired evolutionary optimizers in the quantum hyperspace. The QDMA integrates the superiorities of distributed, memetic, and quantum evolution. Computational experiments are carried out to evaluate the superior performance of QDMA. The results demonstrate the effectiveness of special designs and show that QDMA has greater superiority compared to the compared state-of-the-art algorithms based on Wilcoxon’s rank-sum test. The superiority is attributed not only to good cooperative coevolution of distributed memetic evolutionary model, but also to superior designs of each special component.https://www.sciopen.com/article/10.23919/CSMS.2022.0021distributed evolutionary algorithmmemetic algorithmquantum-inspired evolutionary algorithmquantum distributed memetic algorithm |
| spellingShingle | Guanghui Zhang Wenjing Ma Keyi Xing Lining Xing Kesheng Wang Quantum-Inspired Distributed Memetic Algorithm Complex System Modeling and Simulation distributed evolutionary algorithm memetic algorithm quantum-inspired evolutionary algorithm quantum distributed memetic algorithm |
| title | Quantum-Inspired Distributed Memetic Algorithm |
| title_full | Quantum-Inspired Distributed Memetic Algorithm |
| title_fullStr | Quantum-Inspired Distributed Memetic Algorithm |
| title_full_unstemmed | Quantum-Inspired Distributed Memetic Algorithm |
| title_short | Quantum-Inspired Distributed Memetic Algorithm |
| title_sort | quantum inspired distributed memetic algorithm |
| topic | distributed evolutionary algorithm memetic algorithm quantum-inspired evolutionary algorithm quantum distributed memetic algorithm |
| url | https://www.sciopen.com/article/10.23919/CSMS.2022.0021 |
| work_keys_str_mv | AT guanghuizhang quantuminspireddistributedmemeticalgorithm AT wenjingma quantuminspireddistributedmemeticalgorithm AT keyixing quantuminspireddistributedmemeticalgorithm AT liningxing quantuminspireddistributedmemeticalgorithm AT keshengwang quantuminspireddistributedmemeticalgorithm |