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Economic load dispatch problems with valve-point loading using natural updated harmony search

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Abstract

In this paper, the update process of harmony search (HS) algorithm is modified to improve its concept of diversity. The update process in HS is based on a greedy mechanism in which the new harmony solution, created in each generation, replaces the worst individual in the population, if better. This greedy process could be improved with other updates mechanisms in order to control the diversity perfectly. Three versions of HS have been proposed: (1) Natural Proportional HS ; (2) Natural Tournament HS; (3) Natural Rank HS. These three HS versions employed the natural selection principle of the “survival of the fittest”. Instead of replacing the worst individual in population, any individual can be replaced based on certain criteria. Four versions of economic loading dispatch (ELD) problems with valve point have been used to measure the effect of the newly proposed HS versions. The results show that the new HS versions are very promising for ELD domain. This claim is proved based on the comparative evaluation process where the new HS versions are able to excel the state-of-the-art methods in almost ELD problems used.

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Authors and Affiliations

  1. Department of Information Technology, Al-Huson University College, Al-Balqa Applied University, P.O. Box 50, Al-Huson, Irbid, Jordan

    Mohammed Azmi Al-Betar & Ammar Almomani

  2. Department of Computer Science, Al-Aqsa University, P. O. Box 4051, Gaza, Palestine

    Mohammed A. Awadallah

  3. School of Computer Sciences, Universiti Sains Malaysia, 11800, Pulau Pinang, Malaysia

    Ahamad Tajudin Khader

  4. Department of Computer Science, Faculty of Pure and Applied Sciences, Federal University Wukari, P. M. B. 1029, Wukari, Taraba State, Nigeria

    Asaju La’aro Bolaji

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  1. Mohammed Azmi Al-Betar
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Al-Betar, M.A., Awadallah, M.A., Khader, A.T. et al. Economic load dispatch problems with valve-point loading using natural updated harmony search. Neural Comput & Applic 29, 767–781 (2018). https://doi.org/10.1007/s00521-016-2611-2

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