Short-term scheduling of thermal-electric generators using Lagrangian relaxation
Operations Research
An Improved Genetic Algorithm with Average-bound Crossover and Wavelet Mutation Operations
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Implementing soft computing techniques to solve economic dispatch problem in power systems
Expert Systems with Applications: An International Journal
Nonconvex economic load dispatch using an efficient real-coded genetic algorithm
Applied Soft Computing
Particle swarm optimization with crazy particles for nonconvex economic dispatch
Applied Soft Computing
Nature-Inspired Metaheuristic Algorithms
Nature-Inspired Metaheuristic Algorithms
Solving complex economic load dispatch problems using biogeography-based optimization
Expert Systems with Applications: An International Journal
Firefly algorithm, stochastic test functions and design optimisation
International Journal of Bio-Inspired Computation
Firefly algorithms for multimodal optimization
SAGA'09 Proceedings of the 5th international conference on Stochastic algorithms: foundations and applications
Mixed variable structural optimization using Firefly Algorithm
Computers and Structures
Evolutionary programming techniques for economic load dispatch
IEEE Transactions on Evolutionary Computation
Multiobjective evolutionary algorithms for electric power dispatch problem
IEEE Transactions on Evolutionary Computation
Stability analysis of social foraging swarms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Multimodal size, shape, and topology optimisation of truss structures using the Firefly algorithm
Advances in Engineering Software
Expert Systems with Applications: An International Journal
Bio-inspired optimisation for economic load dispatch: a review
International Journal of Bio-Inspired Computation
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The growing costs of fuel and operation of power generating units warrant improvement of optimization methodologies for economic dispatch (ED) problems. The practical ED problems have non-convex objective functions with equality and inequality constraints that make it much harder to find the global optimum using any mathematical algorithms. Modern optimization algorithms are often meta-heuristic, and they are very promising in solving nonlinear programming problems. This paper presents a novel approach to determining the feasible optimal solution of the ED problems using the recently developed Firefly Algorithm (FA). Many nonlinear characteristics of power generators, and their operational constraints, such as generation limitations, prohibited operating zones, ramp rate limits, transmission loss, and nonlinear cost functions, were all contemplated for practical operation. To demonstrate the efficiency and applicability of the proposed method, we study four ED test systems having non-convex solution spaces and compared with some of the most recently published ED solution methods. The results of this study show that the proposed FA is able to find more economical loads than those determined by other methods. This algorithm is considered to be a promising alternative algorithm for solving the ED problems in practical power systems.