relation: https://khub.utp.edu.my/scholars/5959/
title: Swarm-based mean-variance mapping optimization (MVMOS) for solving non-convex economic dispatch problems
creator: Khoa, T.H.
creator: Vasant, P.M.
creator: Singh, B.S.M.
creator: Dieu, V.N.
description: The practical Economic Dispatch (ED) problems have non-convex objective functions with complex constraints due to the effects of valve point loadings, multiple fuels, and prohibited zones. This leads to difficulty in finding the global optimal solution of the ED problems. This chapter proposes a new swarm-based Mean-Variance Mapping Optimization (MVMOS) for solving the non-convex ED. The proposed algorithm is a new population-based meta-heuristic optimization technique. Its special feature is a mapping function applied for the mutation. The proposed MVMOS is tested on several test systems and the comparisons of numerical obtained results between MVMOS and other optimization techniques are carried out. The comparisons show that the proposed method is more robust and provides better solution quality than most of the other methods. Therefore, the MVMOS is very favorable for solving non-convex ED problems. © 2015, IGI Global. All rights reserved.
publisher: IGI Global
date: 2015
type: Book
type: PeerReviewed
identifier:   Khoa, T.H. and Vasant, P.M. and Singh, B.S.M. and Dieu, V.N.  (2015) Swarm-based mean-variance mapping optimization (MVMOS) for solving non-convex economic dispatch problems.     IGI Global, pp. 211-251.  ISBN 9781466682924; 1466682914; 9781466682917     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957398364&doi=10.4018%2f978-1-4666-8291-7.ch007&partnerID=40&md5=6b898dbbf2ec18646719b25b6c2cbcb0
relation: 10.4018/978-1-4666-8291-7.ch007
identifier: 10.4018/978-1-4666-8291-7.ch007