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Floating search space: A new idea for efficient solving the Economic and emission dispatch problem

Amiri, M., Khanmohammadi, S., Badamchizadeh, M.A.
Energy 2018 v.158 pp. 564-579
algorithms, artificial intelligence, energy, system optimization
Efficient solving of practical optimization problems in important fields like the energy and its peripheral problems has been an ever-growing attractive topic for many academicians and industries during the recent decades. This paper introduces a swarm-based optimization method, namely the Floating Search Space, to solve one of the most important energy problems called the “Economic and Emission Dispatch”. The proposed method, which resizes and floats the allowed search region inside the main search space, is attached to three versions of swarm intelligence-based Optimization algorithms, as a supplementary approach, to enhance their performance and achieve high quality solutions in a more reliable way. The proposed method, which receives online feedbacks from the population to regulate itself and define most promising areas inside the search space is a simple parameter-free technique which can be easily attached to any intelligent optimizer. Simulation results approve that the proposed method is able to obtain competing solutions to the real-world modeled Economic and Emission Dispatch problems by increasing the accuracy, decreasing computational budget, and achieving more robust performance by reducing stagnations and rising success rate.