A comparative study of population-based optimisation algorithms for thrust allocation in dynamic positioning system. (2015)

• Record Type: Journal Article
• Authors: Ren, Fengkun; Wu, Defeng; Yin, Zibin; Zeng, Buhui
• Is Part Of: International journal of modelling, identification and control. Volume 23:Number 2(2015)
• Page Start: 101
• Page End: 111
• Publication Date: 2015
• Subjects: biogeography-based optimisation -- BBO -- genetic algorithms -- particle swarm optimisation -- PSO -- differential evolution -- artificial bee colony -- ABC -- dynamic positioning -- thrust allocation -- deep sea oil exploration -- oil and gas industry; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

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.