TY  - JOUR
SP  - 419
TI  - Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem
N1  - cited By 0; Conference of 4th International Conference on Soft Computing and Data Mining, SCDM 2020 ; Conference Date: 22 January 2020 Through 23 January 2020; Conference Code:235699
AV  - none
EP  - 428
PB  - Springer
SN  - 21945357
ID  - scholars13988
KW  - Data mining; Optimization; Scheduling; Soft computing
KW  -  Bat algorithms; Economic Dispatch; Meta heuristic algorithm; Non-convex; Non-convex economic dispatches; Power generation dispatch; Power generation systems; Pre-mature convergences
KW  -  Electric load dispatching
N2  - Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations. © Springer Nature Switzerland AG 2020.
VL  - 978 AI
JF  - Advances in Intelligent Systems and Computing
A1  - Hussain, K.
A1  - Zhu, W.
A1  - Salleh, M.N.M.
A1  - Ali, H.
A1  - Talpur, N.
A1  - Naseem, R.
A1  - Ahmad, A.
A1  - Ullah, A.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078430728&doi=10.1007%2f978-3-030-36056-6_39&partnerID=40&md5=b98e2c48250e3798b76e065b1b019f39
Y1  - 2020///
ER  -