relation: https://khub.utp.edu.my/scholars/8781/
title: Quantum-inspired computational intelligence for economic emission dispatch problem
creator: Mahdi, F.P.
creator: Vasant, P.
creator: Kallimani, V.
creator: Abdullah-Al-Wadud, M.
creator: Watada, J.
description: 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. © 2017, IGI Global. All rights reserved.
publisher: IGI Global
date: 2017
type: Book
type: PeerReviewed
identifier:   Mahdi, F.P. and Vasant, P. and Kallimani, V. and Abdullah-Al-Wadud, M. and Watada, J.  (2017) Quantum-inspired computational intelligence for economic emission dispatch problem.     IGI Global, pp. 445-468.  ISBN 9781522521297; 1522521283; 9781522521280     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027528924&doi=10.4018%2f978-1-5225-2128-0.ch015&partnerID=40&md5=37c42f4e696c563515ab559d701a70c0
relation: 10.4018/978-1-5225-2128-0.ch015
identifier: 10.4018/978-1-5225-2128-0.ch015