eprintid: 13001
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/30/01
datestamp: 2023-11-10 03:27:33
lastmod: 2023-11-10 03:27:33
status_changed: 2023-11-10 01:50:06
type: book
metadata_visibility: show
creators_name: Rahman, M.A.
creators_name: Vasant, P.M.
creators_name: Watada, J.
creators_name: Sokkalingam, R.
title: Genetic algorithm and particle swarm optimization techniques in supply chain design problems: A survey
ispublished: pub
note: cited By 2
abstract: Metaheuristics has become a top research area. Numerous optimization problems have been solved by metaheuristics as they showed comprehensive improvements to solve these intractable optimization problems. Complex problems like supply chain design problems need strategic decisions, and metaheuristics can intensify the decisions while designing supply chain network. In this chapter, the authors have introduced how nature memetic algorithms (e.g., genetic algorithm and particle swarm algorithms) are implemented to solve supply chain network design problem. A discussion about the recent research in this field shows an important direction to the future research. © 2020, IGI Global.
date: 2020
publisher: IGI Global
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85109446931&doi=10.4018%2f978-1-7998-3645-2.ch019&partnerID=40&md5=a5a34a585a2cabe082e87de746b54db4
id_number: 10.4018/978-1-7998-3645-2.ch019
full_text_status: none
publication: Handbook of Research on Smart Technology Models for Business and Industry
pagerange: 425-438
refereed: TRUE
isbn: 9781799836469; 9781799836452
citation:   Rahman, M.A. and Vasant, P.M. and Watada, J. and Sokkalingam, R.  (2020) Genetic algorithm and particle swarm optimization techniques in supply chain design problems: A survey.     IGI Global, pp. 425-438.  ISBN 9781799836469; 9781799836452