App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 12

Research on dynamic multi-objective cultural tourism service composition optimization based on improved social learning optimization

Hai Yan1
Wang Hanxu1
Liu Zhizhong2
1. School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou Henan 450045, China
2. School of Computer and Control Engineering, Yantai University, Yantai Shandong 264005, China
DOI: 10.19734/j.issn.1001-3695.2026.05.0119

Abstract

Factors such as tourist demand and weather conditions often cause fluctuations in service attributes. These fluctuations can lead to inaccurate change detection, delayed responses, and unstable search performance. To address these problems, this study constructed a dynamic multi-objective optimization model that considered ecological cost, economic benefit, service quality, and tourist experience. Based on this model, this study proposed CC-ISLO, a change-aware closed-loop optimization method based on improved Social Learning Optimization (SLO) . Firstly, it used random sampling and weighted voting to detect changes, and also combined anomaly suppression with a cooldown mechanism to improve detection robustness. Secondly, it combined a multi-feature representative set with trend-adaptive perturbation to respond rapidly to changes. Finally, it improved the spatial operators of SLO to enhance the overall search capability. Experimental results show that it achieves a mean inverted generational distance (MIGD) of 0.0599 (0.0038) and a final-generation hypervolume (HV) of 0.9331 (0.0299) . It significantly outperforms AB-DMOEA, DRVEA, and other algorithms on both metrics. Further results from multiple experiments indicate that CC-ISLO demonstrates strong dynamic tracking accuracy, solution-set coverage, and search stability. It can therefore provide more effective support for dynamic cultural tourism service composition optimization.

Foundation Support

国家自然科学基金面上项目(62273290)
山东省科技发展计划(2025CXPT077)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.05.0119
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 12

Publish History

[2026-08-21] Accepted Paper

Cite This Article

海燕, 王翰旭, 刘志中. 基于改进SLO的动态多目标文旅服务优化组合方法 [J]. 计算机应用研究, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0119. (Hai Yan, Wang Hanxu, Liu Zhizhong. Research on dynamic multi-objective cultural tourism service composition optimization based on improved social learning optimization [J]. Application Research of Computers, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.05.0119. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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