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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Quantum-Inspired Computational Intelligence for Economic Emission Dispatch Problem

Quantum-Inspired Computational Intelligence for Economic Emission Dispatch Problem
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Author(s): Fahad Parvez Mahdi (Universiti Teknologi Petronas, Malaysia), Pandian Vasant (University of Technology Petronas, Malaysia), Vish Kallimani (Universiti Teknologi Petronas, Malaysia), M. Abdullah-Al-Wadud (King Saud University, Saudi Arabia) and Junzo Watada (Universiti Teknologi PETRONAS, Malaysia)
Copyright: 2020
Pages: 24
Source title: Foreign Direct Investments: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-2448-0.ch027

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Abstract

Economic emission dispatch (EED) problems are one of the most crucial problems in power systems. Growing energy demand, limited reserves of fossil fuel and global warming make this topic into the center of discussion and research. In this chapter, we will discuss the use and scope of different quantum inspired computational intelligence (QCI) methods for solving EED problems. We will evaluate each previously used QCI methods for EED problem and discuss their superiority and credibility against other methods. We will also discuss the potentiality of using other quantum inspired CI methods like quantum bat algorithm (QBA), quantum cuckoo search (QCS), and quantum teaching and learning based optimization (QTLBO) technique for further development in this area.

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