A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems
Hunger Games Search (HGS) is a newly developed metaheuristic algorithm that models the hunger-driven activities and behaviors of animals. It incorporates the concept of hunger to devise an adaptive weight that mimics the impact of hunger on each search step. In this paper, a Multi-Stage Adaptive Seq...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10230245/ |
| _version_ | 1797676718807318528 |
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| author | Bihao Zhan Wei Gu |
| author_facet | Bihao Zhan Wei Gu |
| author_sort | Bihao Zhan |
| collection | DOAJ |
| description | Hunger Games Search (HGS) is a newly developed metaheuristic algorithm that models the hunger-driven activities and behaviors of animals. It incorporates the concept of hunger to devise an adaptive weight that mimics the impact of hunger on each search step. In this paper, a Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm (MASPE-HGSA) is proposed to alleviate the shortcomings of the original HGS in terms of insufficient optimization and convergence accuracy. In MASPE-HGSA, a Multi-Stage adaptive sequential parameter exploration is proposed to improve the search performance of the algorithm as well as to increase the search accuracy and global search capability, which can commendably achieve the balance of exploration and exploitation. The effectiveness of MASPE-HGSA is verified by comparing with original HGS algorithm and several classical algorithms using 23 benchmark functions, CEC2014 test set and three advanced algorithmic problems from classical engineering. Experimental results show that the performance of MASPE-HGSA is significantly better than other similar algorithms. The proposed algorithm can effectively search for high-quality solutions and prevent premature convergence, with better convergence robustness than the original HGS algorithm. In addition, an analysis of probability-based algorithm mechanisms approaching zero is presented in this paper from a theoretical perspective, while providing a reference and verification method for the design of algorithm mechanisms. |
| first_indexed | 2024-03-11T22:34:10Z |
| format | Article |
| id | doaj.art-e01e8c56b97444bba16a1ee48edf632b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T22:34:10Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e01e8c56b97444bba16a1ee48edf632b2023-09-22T23:00:51ZengIEEEIEEE Access2169-35362023-01-011110091910094710.1109/ACCESS.2023.330869010230245A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization ProblemsBihao Zhan0Wei Gu1https://orcid.org/0000-0002-7972-5527School of Computer Science, Hubei University of Technology, Wuhan, ChinaSchool of Computer Science, Hubei University of Technology, Wuhan, ChinaHunger Games Search (HGS) is a newly developed metaheuristic algorithm that models the hunger-driven activities and behaviors of animals. It incorporates the concept of hunger to devise an adaptive weight that mimics the impact of hunger on each search step. In this paper, a Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm (MASPE-HGSA) is proposed to alleviate the shortcomings of the original HGS in terms of insufficient optimization and convergence accuracy. In MASPE-HGSA, a Multi-Stage adaptive sequential parameter exploration is proposed to improve the search performance of the algorithm as well as to increase the search accuracy and global search capability, which can commendably achieve the balance of exploration and exploitation. The effectiveness of MASPE-HGSA is verified by comparing with original HGS algorithm and several classical algorithms using 23 benchmark functions, CEC2014 test set and three advanced algorithmic problems from classical engineering. Experimental results show that the performance of MASPE-HGSA is significantly better than other similar algorithms. The proposed algorithm can effectively search for high-quality solutions and prevent premature convergence, with better convergence robustness than the original HGS algorithm. In addition, an analysis of probability-based algorithm mechanisms approaching zero is presented in this paper from a theoretical perspective, while providing a reference and verification method for the design of algorithm mechanisms.https://ieeexplore.ieee.org/document/10230245/Swarm intelligence algorithmshunger games searchmulti-stage adaptive sequential parameter exploration mechanismengineering design problem |
| spellingShingle | Bihao Zhan Wei Gu A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems IEEE Access Swarm intelligence algorithms hunger games search multi-stage adaptive sequential parameter exploration mechanism engineering design problem |
| title | A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems |
| title_full | A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems |
| title_fullStr | A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems |
| title_full_unstemmed | A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems |
| title_short | A Multi-Stage Adaptive Sequential Parameter Exploration Hunger Games Search Algorithm for Solving Complex Optimization Problems |
| title_sort | multi stage adaptive sequential parameter exploration hunger games search algorithm for solving complex optimization problems |
| topic | Swarm intelligence algorithms hunger games search multi-stage adaptive sequential parameter exploration mechanism engineering design problem |
| url | https://ieeexplore.ieee.org/document/10230245/ |
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