This paper presents a novel modified bacterial foraging technique (BFT) to solve economic load dispatch (ELD) problems. BFT is already used for optimization problems, and performance of basic BFT for small problems with moderate dimension and searching space is satisfactory. Search space and complexity grow exponentially in scalable ELD problems, and the basic BFT is not suitable to solve the high dimensional ELD problems, as cells move randomly in basic BFT, and swarming is not sufficiently achieved by cell-to-cell attraction and repelling effects for ELD. However, chemotaxis, swimming, reproduction and elimination-dispersal steps of BFT are very promising. On the other hand, particles move toward promising locations depending on best values from memory and knowledge in particle swarm optimization (PSO). Therefore, best cell (or particle) biased velocity (vector) is added to the random velocity of BFT to reduce randomness in movement (evolution) and to increase swarming in the proposed method to solve ELD. Finally, a data set from a benchmark system is used to show the effectiveness of the proposed method and the results are compared with other methods.
A. Y. Saber and G. K. Venayagamoorthy, "Economic Load Dispatch Using Bacterial Foraging Technique with Particle Swarm Optimization Biased Evolution," Proceedings of the 2008 IEEE Swarm Intelligence Symposium (2008, St. Louis, MO), Institute of Electrical and Electronics Engineers (IEEE), Sep 2008.
The definitive version is available at https://doi.org/10.1109/SIS.2008.4668291
2008 IEEE Swarm Intelligence Symposium (2008: Sep. 21-23, St. Louis, MO)
Electrical and Computer Engineering
Keywords and Phrases
Bacterial Foraging Technique; Economic Load Dispatch; Particle Swarm Optimization
Article - Conference proceedings
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