scholarly journals PARTICLE SWARM OPTIMIZATION TECHNIQUE FOR DYNAMIC ECONOMIC DISPATCH

2016 ◽  
Vol 05 (05) ◽  
pp. 460-466 ◽  
Author(s):  
K. Srikanth .
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Particle Swarm Optimization Technique ◽  
Dynamic Economic Dispatch

scholarly journals Dynamic Economic Dispatch Assessment Using Particle Swarm Optimization Technique

2018 ◽  
Vol 7 (3) ◽  
pp. 458-464
Author(s):  
Muhammad Murtadha Othman ◽  
Mohd Affendi Ismail Salim ◽  
Ismail Musirin ◽  
Nur Ashida Salim ◽  
Mohammad Lutfi Othman
Keyword(s):  
Particle Swarm Optimization ◽  
Power System ◽  
Transmission Lines ◽  
Optimization Technique ◽  
Economic Dispatch ◽  
Particle Swarm ◽  
Optimal Operation ◽  
Swarm Optimization ◽  
Particle Swarm Optimization Technique ◽  
Dynamic Economic Dispatch

This paper presents the application of particle swarm optimization (PSO) technique for solving the dynamic economic dispatch (DED) problem. The DED is one of the main functions in power system planning in order to obtain optimum power system operation and control. It determines the optimal operation of generating units at every predicted load demands over a certain period of time. The optimum operation of generating units is obtained by referring to the minimum total generation cost while the system is operating within its limits. The DED based PSO technique is tested on a 9-bus system containing of three generator bus, six load bus and twelve transmission lines.

Materialized View Selection Using Swap Operator Based Particle Swarm Optimization

2021 ◽  
Vol 13 (1) ◽  
pp. 58-73
Author(s):  
Amit Kumar ◽  
T. V. Vijay Kumar
Keyword(s):  
Particle Swarm Optimization ◽  
Data Warehouse ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Selection Problem ◽  
Data Repository ◽  
Swarm Optimization ◽  
View Selection ◽  
Particle Swarm Optimization Technique ◽  
Swap Operator

The data warehouse is a key data repository of any business enterprise that stores enormous historical data meant for answering analytical queries. These queries need to be processed efficiently in order to make efficient and timely decisions. One way to achieve this is by materializing views over a data warehouse. An n-dimensional star schema can be mapped into an n-dimensional lattice from which Top-K views can be selected for materialization. Selection of such Top-K views is an NP-Hard problem. Several metaheuristic algorithms have been used to address this view selection problem. In this paper, a swap operator-based particle swarm optimization technique has been adapted to address such a view selection problem.

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