Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem

© 2016 Mapping Sciences Institute, Australia and Surveying and Spatial Sciences Institute. This paper introduces meta-heuristics and its application to an employee transportation problem for a case study of a hard disk drive company. The objective of the development is to demonstrate improved route...

Full description

Saved in:

Bibliographic Details
Main Authors:	Saeheaw T., Charoenchai N.
Format:	Journal
Published:	2017
Online Access:	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85002489596&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/40285
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Chiang Mai University

id	th-cmuir.6653943832-40285
record_format	dspace
spelling	th-cmuir.6653943832-402852017-09-28T04:08:41Z Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem Saeheaw T. Charoenchai N. © 2016 Mapping Sciences Institute, Australia and Surveying and Spatial Sciences Institute. This paper introduces meta-heuristics and its application to an employee transportation problem for a case study of a hard disk drive company. The objective of the development is to demonstrate improved route planning and fleet assignment to serve all employees in terms of cost savings. A GIS-based employee transportation system is created to design the shortest routes with feasible fleet allocation. The proposed meta-heuristics–central force optimization (CFO), chemical reaction optimization (CRO), and a parallel CFO-CRO–are compared with cuckoo search to validate the performance. The proposed algorithms can effectively determine the most feasible routes. The system is easy to use and capable of handling complex vehicle routing problems. 2017-09-28T04:08:41Z 2017-09-28T04:08:41Z 2 Journal 14498596 2-s2.0-85002489596 10.1080/14498596.2016.1256237 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85002489596&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/40285
institution	Chiang Mai University
building	Chiang Mai University Library
country	Thailand
collection	CMU Intellectual Repository
description	© 2016 Mapping Sciences Institute, Australia and Surveying and Spatial Sciences Institute. This paper introduces meta-heuristics and its application to an employee transportation problem for a case study of a hard disk drive company. The objective of the development is to demonstrate improved route planning and fleet assignment to serve all employees in terms of cost savings. A GIS-based employee transportation system is created to design the shortest routes with feasible fleet allocation. The proposed meta-heuristics–central force optimization (CFO), chemical reaction optimization (CRO), and a parallel CFO-CRO–are compared with cuckoo search to validate the performance. The proposed algorithms can effectively determine the most feasible routes. The system is easy to use and capable of handling complex vehicle routing problems.
format	Journal
author	Saeheaw T. Charoenchai N.
spellingShingle	Saeheaw T. Charoenchai N. Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
author_facet	Saeheaw T. Charoenchai N.
author_sort	Saeheaw T.
title	Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
title_short	Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
title_full	Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
title_fullStr	Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
title_full_unstemmed	Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
title_sort	integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem
publishDate	2017
url	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85002489596&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/40285
_version_	1681421781612625920

Integration of geographical information systems, meta-heuristics and optimization models for the employee transportation problem

Similar Items