A comparative study of population-based optimisation algorithms for thrust allocation in dynamic positioning system
| Autor: | Defeng Wu, Fengkun Ren, Zibin Yin, Buhui Zeng |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Mathematical optimization
Engineering education.field_of_study business.industry Applied Mathematics Population Particle swarm optimization Thrust Computer Science Applications Modeling and Simulation Differential evolution Genetic algorithm Key (cryptography) Dynamic positioning Optimisation algorithm business education |
| Zdroj: | International Journal of Modelling, Identification and Control. 23:101 |
| ISSN: | 1746-6180 1746-6172 |
| DOI: | 10.1504/ijmic.2015.068873 |
| Popis: | Dynamic positioning (DP) system is a key technology and a necessary equipment to solve the problem of deep-sea oil exploration and exploitation and the thrust allocation (TA) system is an important part of DP system. Currently, population-based optimisation algorithms are an important method to solve the TA problem. In this work, population-based optimisation algorithms [artificial bee colony (ABC) algorithm, biogeography-based optimisation (BBO), differential evolution (DE) algorithm, genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm[ are used for optimising the thrust allocation (TA) problem of dynamic positioning (DP) system and the results are analysed and compared. Results show that the performance of the DE is better than or similar to those of other population-based algorithms. |
| Databáze: | OpenAIRE |
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