Two popular particle swarm optimization (PSO) formulations; fuzzy–PSO (FPSO) and chaos–PSO (CPSO) have previously been studied in the literature. The charisma factor in FPSO gives the ability to track the particles which are closest to the optimum. CPSO has been aimed to search the area by using the chaotic maps. These two different algorithms are shown to demonstrate sufficient performance ind...

We describe in this paper a new hybrid approach for optimization combining Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) using Fuzzy Logic to integrate the results. The new evolutionary method combines the advantages of PSO and GA to give us an improved FPSO+FGA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible. The new hybrid ...

This report addresses three aspects of work and health among offshore personnel, drawing on data collected between 1995 and 2002. • A detailed survey of North Sea personnel (N=470) working on 'Floating Production, Storage and Offloading' (FPSO) installations in 2002 is reported. Significant differences were found across installations and across job types in a wide range of psychosocial measures...

The standard Particle Swarm Optimization (PSO) algorithm is a novel evolutionary algorithm in which each particle studies its own previous best solution and the group’s previous best to optimize problems. One problem exists in PSO is its tendency of trapping into local optima. In this paper, a fast particle swarm optimization (FPSO) algorithm is proposed by combining PSO and the Cauchy mutation...

Particle swarm optimization (PSO) and fast evolutionary programming (FEP) are two widely used population-based optimisation algorithms. The ideas behind these two algorithms are quite different. While PSO is very efficient in local converging to an optimum due to its use of directional information, FEP is better at global exploration and finding a near optimum globally. This paper proposes a no...

Particle swarm optimization (PSO) is a popular and robust strategy for optimization problems. One main difficulty in applying PSO to real-world applications is that PSO usually need a large number of fitness evaluations before a satisfying result can be obtained. This paper introduces a new ”fast particle swarm optimization” (FPSO) that does not evaluate all new positions owning a fitness and a...

In this paper, an offshore process front end engineering design (FEED) method is systematically introduced and reviewed to enable efficient offshore oil and gas production plant engineering. An integrated process engineering environment is also presented for the topside systems of a liquefied natural gas floating production, storage, and offloading (LNG FPSO) unit, based on the concepts and pro...

Underwater acoustic recordings of six Floating Production Storage and Offloading (FPSO) vessels moored off Western Australia are presented. Monopole source spectra were computed for use in environmental impact assessments of underwater noise. Given that operations on the FPSOs varied over the period of recording, and were sometimes unknown, the authors present a statistical approach to noise le...

Numerous Acts of Parliament and Statutory Instruments which apply to Floating Production, Storage and Offloading (FPSO) developments in the United Kingdom Continental Shelf (UKCS), covering a wide range of issues including health, technical safety, work place safety, lifting operations, environmental protection and pollution prevention and control, are described. A comprehensive study of system...

Multimodal optimization problems pose a great challenge of locating multiple optima simultaneously in the search space to the particle swarm optimization (PSO) community. In this paper, the motion principle of particles in PSO is extended by using the near-neighbor effect in mechanical theory, which is a universal phenomenon in nature and society. In the proposed near-neighbor effect based forc...