Evolutionary programming techniques for economic load dispatch
IEEE Transactions on Evolutionary Computation
International Journal of Wireless and Mobile Computing
Social emotional optimisation algorithm with emotional model
International Journal of Computational Science and Engineering
International Journal of Wireless and Mobile Computing
Social emotional optimisation algorithm with Levy distribution
International Journal of Wireless and Mobile Computing
Time-varying social emotional optimisation algorithm
International Journal of Computing Science and Mathematics
Reactive power optimisation of power system with APPM
International Journal of Computing Science and Mathematics
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Seeker optimisation algorithm (SOA), a novel heuristic population-based search algorithm, is utilised in this paper to solve different economic load dispatch (ELD) problems of thermal power units. In the SOA, the act of human searching capability and understanding are exploited for the purpose of optimisation. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the algorithm has been tested on four different small, as well as, large-scale test power systems to solve the ELD problems. The outcome of the present work is to establish the SOA as a promising alternative approach to solve the ELD problems in practical power systems. Both the near optimality of the solution and the convergence speed of the algorithm are promising. The results obtained by the SOA are compared to those published in the recent literatures to establish its superiority.