[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Roy et al., 2013 - Google Patents

Modified shuffled frog leaping algorithm with genetic algorithm crossover for solving economic load dispatch problem with valve-point effect

Roy et al., 2013

Document ID
4687707271787294054
Author
Roy P
Roy P
Chakrabarti A
Publication year
Publication venue
Applied Soft Computing

External Links

Snippet

This paper addresses a hybrid solution methodology involving modified shuffled frog leaping algorithm (MSFLA) with genetic algorithm (GA) crossover for the economic load dispatch problem of generating units considering the valve-point effects. The MSFLA uses a …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/04Architectures, e.g. interconnection topology
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/12Computer systems based on biological models using genetic models
    • G06N3/126Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F2217/00Indexing scheme relating to computer aided design [CAD]
    • G06F2217/78Power analysis and optimization
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/04Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Roy et al. Modified shuffled frog leaping algorithm with genetic algorithm crossover for solving economic load dispatch problem with valve-point effect
Cai et al. A hybrid CPSO–SQP method for economic dispatch considering the valve-point effects
Jeyakumar et al. Particle swarm optimization for various types of economic dispatch problems
Niknam et al. A new fuzzy adaptive particle swarm optimization for non-smooth economic dispatch
Li et al. A hybrid artificial bee colony assisted differential evolution algorithm for optimal reactive power flow
Mohammadi-Ivatloo et al. Iteration PSO with time varying acceleration coefficients for solving non-convex economic dispatch problems
Shabanpour-Haghighi et al. A modified teaching–learning based optimization for multi-objective optimal power flow problem
Singh et al. Optimal allocation of capacitors in distribution systems using particle swarm optimization
Ghasemi et al. A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems
Abdelaziz et al. Distribution systems reconfiguration using a modified particle swarm optimization algorithm
Basu et al. Cuckoo search algorithm for economic dispatch
Kumar et al. A hybrid multi-agent based particle swarm optimization algorithm for economic power dispatch
Sayah et al. A hybrid differential evolution algorithm based on particle swarm optimization for nonconvex economic dispatch problems
Hosseinnezhad et al. Economic load dispatch using θ-PSO
Palanichamy et al. Analytical solution for combined economic and emissions dispatch
He et al. A novel algorithm for economic load dispatch of power systems
Balaji et al. Mathematical approach assisted differential evolution for generator maintenance scheduling
Fesanghary et al. A novel meta-heuristic optimization methodology for solving various types of economic dispatch problem
Hamedi Solving the combined economic load and emission dispatch problems using new heuristic algorithm
Sun et al. Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method
Bhattacharjee et al. Backtracking search optimization based economic environmental power dispatch problems
Zhou et al. Multi-objective artificial bee colony algorithm for short-term scheduling of hydrothermal system
Safdarian et al. Temporal decomposition for security-constrained unit commitment
Hardiansyah et al. Solving economic load dispatch problem using particle swarm optimization technique
Karthikeyan et al. A new approach to the solution of economic dispatch using particle swarm optimization with simulated annealing