Abstract
This article is to presents an improved differential evolution (DE) via memory-based mechanism of particle swarm optimization (PSO). Due to uses the memory concept of PSO, the proposed DE is termed as ‘memory-based DE’ where new mutation and crossover operators are introduced. This proposed technique is validated on three typical benchmark functions namely, Rosenbrock, Rastrigrin and Griewank, and then implemented on three different test systems (3, 6 and 15 unit) of economic dispatch (ED) problem. Experimental results prove that the proposed technique produces faster and more accurate solutions than traditional DE and PSO with the other state-of-the-art algorithms.
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Parouha, R.P., Das, K.N. (2020). An Upgraded Differential Evolution via Memory-Based Mechanism for Economic Dispatch. In: Nagar, A., Deep, K., Bansal, J., Das, K. (eds) Soft Computing for Problem Solving 2019 . Advances in Intelligent Systems and Computing, vol 1138. Springer, Singapore. https://doi.org/10.1007/978-981-15-3290-0_5
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DOI: https://doi.org/10.1007/978-981-15-3290-0_5
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