Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

Vlachogiannis, John G.; Lee, Kwang Y.

doi:10.1016/j.eswa.2009.02.079

Cited by 29 publications

(6 citation statements)

References 21 publications

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“…If solution space of optimisation problem is D dimensions, space vector

is presented as

-th element, where

is location of

-th element,

and also a conceivable explanation. It is being broadly used for solving variable optimization problems as it is very easy to understand and has great convergence rapidity [11] , [16] , [43] , [49] . In addition to SVM, PSO is presented for obtaining optimum constraints in SVM.…”

Section: Methodsmentioning

confidence: 99%

Prediction of Flood Discharge Using Hybrid PSO-SVM Algorithm in Barak River Basin

2023

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“…If solution space of optimisation problem is D dimensions, space vector

is presented as

-th element, where

is location of

-th element,

Section: Methodsmentioning

confidence: 99%

Prediction of Flood Discharge Using Hybrid PSO-SVM Algorithm in Barak River Basin

2023

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“…Solutions generated by the algorithm may be infeasible because the constraints may be violated [49]. Several methods are used to handle the constraint of optimization problem such as specific crossover operator and penalty method.…”

Section: Solutionmentioning

confidence: 99%

A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization

Wang

Zeng

2011

Inf Technol Manag

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In this paper, we studied a substage-zoning filling design problem, which is considered as a complex problem with numerous tasks such as construction planning, dam access road and borrow placement, workspace filling, and construction project management. In analyzing workflows and the mechanism of substage-zoning filling, not only the above-mentioned tasks are considered, but also the environmental factors such as rainfall and hydrology characteristic temperature are taken into account. In this study, an optimization model for dam filling which aimed at reducing the disequilibrium degree of filling intensity was proposed; in addition, a technique based on particle swarm optimization was introduced as the basis of a decision support system for rock-fill dams. The system has been employed in a water conservancy and hydropower project which shows that the system is able to provide quality decision support and facilitate the rock-fill dam construction effectively.

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“…Ever since the inception of PSO in 1995, a significant number of modifications have been made to the basic algorithm for realizing performance improvements [6]. We use quantum discrete particle swarm optimization to solve this problem.…”

Section: Modelling the Problemmentioning

confidence: 99%

Particle swarm optimization-based machine arrangement for filling construction of rock-fill dams

Zeng

Wang

et al. 2009

2009 IEEE International Conference on Industrial Engineering and Engineering Management

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The factors that can influence the equipment optimization in filling construction of rock-fill dam are explained by analyzing the filling system of rock-fill dams in this paper, and an optimization model for equipment organization of fill construction of rock-fill dam is established, in which the minimum of unbalanced degree of filling intensity is taken as the objective function with constraint. The quantum discrete particle swarm optimization is used in the model solution. Based on the optimization model and algorithm, the hydraulic engineering construction management decision support system is developed by using an object-oriented methodology. The system is applied to a practical project successfully to obtain the optimum solution of equipment organization.

show abstract

Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

Cited by 29 publications

References 21 publications

Prediction of Flood Discharge Using Hybrid PSO-SVM Algorithm in Barak River Basin

Prediction of Flood Discharge Using Hybrid PSO-SVM Algorithm in Barak River Basin

A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization

Particle swarm optimization-based machine arrangement for filling construction of rock-fill dams

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