An Elastic Collision Seeker Optimization Algorithm for Optimization Constrained Engineering Problems
Shaomi Duan,
Huilong Luo,
Haipeng Liu and
Aditya Rio Prabowo
Mathematical Problems in Engineering, 2022, vol. 2022, 1-28
Abstract:
To improve the seeker optimization algorithm (SOA), an elastic collision seeker optimization algorithm (ECSOA) was proposed. The ECSOA evolves some individuals in three situations: completely elastic collision, completely inelastic collision, and non-completely elastic collision. These strategies enhance the individuals’ diversity and avert falling into the local optimum. The ECSOA is compared with the particle swarm optimization (PSO), the simulated annealing and genetic algorithm (SA_GA), the gravitational search algorithm (GSA), the sine cosine algorithm (SCA), the multiverse optimizer (MVO), and the seeker optimization algorithm (SOA); then, fifteen benchmark functions, four PID control parameter models, and six constrained engineering optimization problems were selected for the experiment. According to the experimental results, the ECSOA can be used in the benchmark functions, the PID control parameter optimization, and the optimization constrained engineering problems. The optimization ability and robustness of ECSOA are better.
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/1344667.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/1344667.xml (application/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1344667
DOI: 10.1155/2022/1344667
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().