Correction: Refaat et al. Multi-stage dynamic transmission network expansion planning using LSHADE-SPACMA. Appl. sci. 2021, 11, 2155

Mohamed M. Refaat, Shady H.E.Abdel Aleem, Yousry Atia, Ziad M. Ali, Mahmoud M. Sayed

Research output: Contribution to journalComment/debate

Abstract

The authors wish to make the following corrections to this paper [1]. Referring to the text of the paper [1], we made some changes to confirm that the purpose of the paper was not the development of LSHADE-SPACMA but solving a multi-stage dynamic transmission network expansion planning problem considering the N-1 reliability constraint, using this algorithm. The corrections were as follows: • In the abstract, the sentence “The linear population size reduction—Success-History-based Differential Evolution with semi-parameter adaptation (LSHADE-SPA) hybrid— covariance matrix adaptation evolution strategy (CMA-ES) algorithm (LSHADE-SPACMA)—is proposed to solve the problem” is replaced with “The linear population size reduction—Success-History-based Differential Evolution with semi-parameter adaptation (LSHADE-SPA) hybrid—covariance matrix adaptation evolution strategy (CMA-ES) algorithm (LSHADE-SPACMA)—is applied to solve the problem”. • In the introduction, the sentence “The present study developed a new a meta-heuristic algorithm called LSHADE-SPACMA to solve a MSDTNEP for the West Delta Network (WDN) up to year 2040 with an embedded N-1 security constraint. The semi-adaptive nature of LSHADE-SPACMA improved the exploration capability and exploitation tendency of the algorithm’s ability to avoid local optima stagnation” is replaced with “The present study employed a meta-heuristic algorithm called LSHADE-SPACMA to solve a MSDTNEP for the West Delta Network (WDN) up to year 2040 with an embedded N-1 security constraint. The semi-adaptive nature of LSHADE-SPACMA improved the exploration capability and exploitation tendency of the algorithm’s ability to avoid local optima stagnation [26]”. • In Section 4: the sentences “In SHADE [26], a history-based parameter adaptation scheme was implemented and considered successful on a wide range of optimization issues. The current work uses a slightly changed version of the initial SHADE algorithm with a fine-tuning of specific parameters borrowed from [26]” are replaced with “In Mohamed et al. [26], a semi-parameter adaptation scheme was implemented to enhance LSHADE technique’s performance. Besides, a hybridization strategy between LSHADE-SPA and CMA-ES was presented and considered successful on a wide range of optimization issues”. The authors express their apologies to the readers for any inconvenience resulted from this correction. It is important to point out that these changes do not affect our study’s results and involve no changes or modifications to the original data supporting our results. The original manuscript, to which this correction refers, will remain online on the article webpage.

Original languageEnglish
Article number6071
JournalApplied Sciences (Switzerland)
Volume11
Issue number13
DOIs
StatePublished - 1 Jul 2021

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