ArticleiScience2023
Advanced slime mould algorithm incorporating differential evolution and Powell mechanism for engineering design.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A multi-strategy integrated improved nutcracker optimization algorithm and its applications in water conservancy engineering.iScience · 2026Article
- An Enhanced Slime Mould Algorithm Based on Best-Worst Management for Numerical Optimization Problems.Biomimetics (Basel, Switzerland) · 2025Article
- IA-DTPSO: A Multi-Strategy Integrated Particle Swarm Optimization for Predicting the Total Urban Water Resources in China.Biomimetics (Basel, Switzerland) · 2025Article
- Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration.Bioengineering (Basel, Switzerland) · 2024Article
- IRIME: Mitigating exploitation-exploration imbalance in RIME optimization for feature selection.iScience · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
The slime mould algorithm (SMA) is a population-based swarm intelligence optimization algorithm that simulates the oscillatory foraging behavior of slime moulds. To overcome its drawbacks of slow convergence speed and premature convergence, this paper proposes an improved algorithm named PSMADE, which integrates the differential evolution algorithm (DE) and the Powell mechanism. PSMADE utilizes crossover and mutation operations of DE to enhance individual diversity and improve global search capability. Additionally, it incorporates the Powell mechanism with a taboo table to strengthen local search and facilitate convergence toward better solutions. The performance of PSMADE is evaluated by comparing it with 14 metaheuristic algorithms (MA) and 15 improved MAs on the CEC 2014 benchmarks, as well as solving four constrained real-world engineering problems. Experimental results demonstrate that PSMADE effectively compensates for the limitations of SMA and exhibits outstanding performance in solving various complex problems, showing potential as an effective problem-solving tool.
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Registered trials
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