Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
A review of particle swarm optimization. Part I: background and development
Natural Computing: an international journal
A hybrid differential evolution method for dynamic economic dispatch with valve-point effects
Expert Systems with Applications: An International Journal
Optimal scheduling of multiple dam system using harmony search algorithm
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
IEEE Transactions on Evolutionary Computation
An Intelligent Tuned Harmony Search algorithm for optimisation
Information Sciences: an International Journal
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
A harmony search algorithm for nurse rostering problems
Information Sciences: an International Journal
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
Hybridising harmony search with a Markov blanket for gene selection problems
Information Sciences: an International Journal
Bio-inspired optimisation for economic load dispatch: a review
International Journal of Bio-Inspired Computation
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This paper presents the hybrid harmony search algorithm with swarm intelligence (HHS) to solve the dynamic economic load dispatch problem. Harmony Search (HS) is a recently developed derivative-free, meta-heuristic optimization algorithm, which draws inspiration from the musical process of searching for a perfect state of harmony. This work is an attempt to hybridize the HS algorithm with the powerful population based algorithm PSO for a better convergence of the proposed algorithm. The main aim of dynamic economic load dispatch problem is to find out the optimal generation schedule of the generators corresponding to the most economical operating point of the system over the considered timing horizon. The proposed algorithm also takes care of different constraints like power balance, ramp rate limits and generation limits by using penalty function method. Simulations were performed over various standard test systems with 5 units, 10 units and 30 units and a comparative study is carried out with other recently reported results. The findings affirmed the robustness and proficiency of the proposed methodology over other existing techniques.