caa a22 4500 605469466 CHVBK 20210128100322.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s00500-014-1273-1 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1273-1 Dynamic optimization facilitated by the memory tree [Elektronische Daten] [Tao Zhu, Wenjian Luo, Lihua Yue] Memorizing the past information for later environments is an effective and widely employed approach to optimize dynamic problems. Although the existing explicit memories for dynamic optimization differ widely in the literature, all of them organize memory entries in a linear list. This naive structure leads to problems, such as heavy computational overhead and small memory capacity, and thus restricts the performance of the memories. In this paper, the binary space partition tree is adopted to organize the memory entries, and then a memory tree is constructed. The memory tree partitions the search space into regions. In order to make use of the memory tree, a neighbor shift strategy is proposed. When a new individual is generated in a region that has never been visited since the last change, the new individual is shifted to the neighboring memory individual of that region, if it is less fit than the memory individual. The proposed approach can be easily combined with many population-based algorithms for dynamic optimization in the real space. As examples, the proposed approach was combined with a basic particle swarm optimizer and two state-of-the-art dynamic optimizers. The experimental results showed that it significantly enhanced the performance of the three optimizers on various test problems. The proposed approach demonstrates the importance of memory structure in memory approaches. Springer-Verlag Berlin Heidelberg, 2014 Dynamic optimization problem nationallicence Population-based algorithms nationallicence Memory nationallicence Memory structure nationallicence Binary space partition tree nationallicence Zhu Tao Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut Luo Wenjian Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut Yue Lihua Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut Soft Computing Springer Berlin Heidelberg 19/3(2015-03-01), 547-566 1432-7643 19:3<547 2015 19 500 https://doi.org/10.1007/s00500-014-1273-1 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1273-1 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhu Tao Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut NATIONALLICENCE 700 1- Luo Wenjian Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut NATIONALLICENCE 700 1- Yue Lihua Anhui Province Key Laboratory of Software Engineering in Computing and Communication, School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, Anhui, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/3(2015-03-01), 547-566 1432-7643 19:3<547 2015 19 500