eprintid: 8781
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/87/81
datestamp: 2023-11-09 16:20:42
lastmod: 2023-11-09 16:20:42
status_changed: 2023-11-09 16:13:30
type: book
metadata_visibility: show
creators_name: Mahdi, F.P.
creators_name: Vasant, P.
creators_name: Kallimani, V.
creators_name: Abdullah-Al-Wadud, M.
creators_name: Watada, J.
title: Quantum-inspired computational intelligence for economic emission dispatch problem
ispublished: pub
keywords: Electric load dispatching; Fossil fuels; Global warming; Optimization; Proven reserves, Bat algorithms; Cuckoo searches; Economic-emission dispatch; Energy demands; Teaching and learning, Problem solving
note: cited By 2
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. © 2017, IGI Global. All rights reserved.
date: 2017
publisher: IGI Global
official_url: 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
id_number: 10.4018/978-1-5225-2128-0.ch015
full_text_status: none
publication: Handbook of Research on Soft Computing and Nature-Inspired Algorithms
pagerange: 445-468
refereed: TRUE
isbn: 9781522521297; 1522521283; 9781522521280
citation:   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