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Bio-inspired heuristics hybrid with sequential quadratic programming and interior-point methods for reliable treatment of economic load dispatch problem

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Abstract

In the present study, bio-inspired computational heuristics are exploited for finding the solution of economic load dispatch (ELD) problem with valve point loading effect using variants of genetic algorithm (GA) hybrid with sequential quadratic programming (SQP) and interior-point algorithms (IPAs). Variants of GAs are constructed using different sets of routines for its fundamental operators in order to explore the entire search space for global optimum solutions while SQP and IPA are integrated with GAs for rapid local convergence. Nine variants of each design scheme based on GAs, GA-SQP and GA-IPAs are applied on three different ELD problems of thermal power plant systems. Comparative studies of the proposed schemes are performed through the results of statistical performance indices in order to establish the worth and effectiveness in terms of accuracy, convergence and complexity measures.

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Authors and Affiliations

  1. Department of Electrical Engineering, COMSATS Institute of Information Technology, Attock, Pakistan

    Muhammad Asif Zahoor Raja & Usman Ahmed

  2. Department of Computer and Information Science, Pakistan Institute of Engineering and Applied Sciences, Nilore, Pakistan

    Aneela Zameer

  3. Department of Economics, Federal Urdu University of Arts Science and Technology, Islamabad, Pakistan

    Adiqa Kausar Kiani

  4. Department of Electrical Engineering, International Islamic University, Islamabad, Pakistan

    Naveed Ishtiaq Chaudhary

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  1. Muhammad Asif Zahoor Raja
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Correspondence to Naveed Ishtiaq Chaudhary.

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Raja, M.A.Z., Ahmed, U., Zameer, A. et al. Bio-inspired heuristics hybrid with sequential quadratic programming and interior-point methods for reliable treatment of economic load dispatch problem. Neural Comput & Applic 31 (Suppl 1), 447–475 (2019). https://doi.org/10.1007/s00521-017-3019-3

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