A hybrid engineering algorithm of the seeker algorithm and particle swarm optimization
نویسندگان
چکیده
Abstract A newly hybrid algorithm is proposed based on the combination of seeker optimization and particle swarm optimization. The a double population evolution strategy, populations individuals are evolved from separately. employ an information sharing mechanism to implement coevolution. enhances individuals’ diversity averts fall into local optimum. compared with optimization, simulated annealing genetic algorithm, dragonfly brain storming gravitational search sine cosine salp multi-verse optimizer, then 15 benchmark functions, five proportional integral differential control parameters models, six constrained engineering problems selected for experiment. According experimental results, can be used in problems. ability robustness better.
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ژورنال
عنوان ژورنال: MP MATERIALPRUEFUNG - MP MATERIALS TESTING
سال: 2022
ISSN: ['2195-8572', '0025-5300']
DOI: https://doi.org/10.1515/mt-2021-2138