Please use this identifier to cite or link to this item:
|dc.contributor.author||Mohd Sidek, L.B.||en_US|
|dc.description.abstract||Particle swarm optimisation (PSO) is a very well-known method and has a strong background in optimisation filed to solve different non-linear, complex problems especially in creating the reservoir release policies. This research modified the particle updating process of the standard PSO algorithm by including the passive congregation (PC) theory. The passive congregation theory of natural being's social behaviour is adopted to updated the standard PSO algorithm and used to develop and optimise a reservoir release policy for monthly basis. The inflow data to the dam/reservoir has categorised into three different categories (High, medium and low). The problem is formulated on correspondence to the release and capacity constraints. Water deficit from the release is aimed to be minimised and formulated as the main objective function. Monthly releases are taken as the main objective variables and are essentially control the water deficit of the process. The standard form of PSO then compared with the updated version and the results is analysed by adopting different performance measuring indicators such as reliability, vulnerability and resilience. The results showed that the updated PSO-PC is more capable of the standard PSO (5% more reliable; 0.02 less vulnerable and 1.5 more resilience) in providing optimum results for a reservoir system. © 2018 Authors.||-|
|dc.title||Passive congregation theory for particle swarm optimization (PSO): An application in reservoir system operation||en_US|
|Appears in Collections:||UNITEN Scholarly Publication|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.