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

Enhanced crested porcupine optimization (ecpo) algorithm based on Heterogeneous parallel computing and game learning

Lai Zhaolin1,2
Li Guangyuan1,2
Ding Hong1,2
Jiang Caoqing1,2
Yang Shuyun1
Lan Yanfeng1
1. School of Big Data and Artificial Intelligence, Guangxi University of Finance and Economics, Nanning 530003, China
2. Guangxi Key Laboratory of Big Data in Finance and Economics, Nanning 530003, China
DOI: 10.19734/j.issn.1001-3695.2026.04.0115

Abstract

Swarm intelligence optimization algorithms possess strong global exploration capability and are important methods for solving complex optimization problems. However, the scale of optimization problems has grown rapidly with technological advances. To address the low search performance and high computational cost of the original Crested Porcupine Optimizer (CPO) on large-scale problems, this paper proposes an enhanced CPO (ECPO) algorithm. The ECPO introduces a minimum-entropy chaotic spiral mapping to improve population initialization, constructs a game-learning model for adaptive strategy selection, and designs a CPU-GPU heterogeneous parallel computing architecture to enhance computational efficiency. This paper also provides theoretical convergence analysis and time complexity analysis for the proposed algorithm. Experiments are conducted on large-scale benchmark functions with dimension 10000, and Wilcoxon and Friedman tests are employed to analyze the significance and ranking of the results. Experimental results demonstrate that ECPO outperforms other compared algorithms in overall performance on large-scale optimization problems. Furthermore, applying ECPO to housing price prediction further verifies its practical application value.

Foundation Support

国家自然科学基金资助项目(62441209)
广西自然科学基金资助项目(2024JJA170275)
广西高校人文社会科学重点研究基地向海经济研究院资助项目(XHYB013)
广西向海经济研究人才小高地资助项目
广西向海经济智能信息系统分析与决策重点实验室资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.04.0115
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 12

Publish History

[2026-08-04] Accepted Paper

Cite This Article

赖兆林, 李广原, 丁红, 等. 基于异构并行计算及博弈学习的冠豪猪优化算法 [J]. 计算机应用研究, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.04.0115. (Lai Zhaolin, Li Guangyuan, Ding Hong, et al. Enhanced crested porcupine optimization (ecpo) algorithm based on Heterogeneous parallel computing and game learning [J]. Application Research of Computers, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.04.0115. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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