Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search
This study considers a version of the stochastic vehicle routing problem where customer demands are random variables with known probability distribution. A new scheme based on a hybrid GA and Tabu Search heuristic is proposed for this problem under a priori approach with preventive restocking. The r...
Saved in:
Main Authors: | , |
---|---|
Format: | Article |
Published: |
Science Publications
2008
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/8402/ http://www.scipub.org/fulltext/jms2/jms243161-167.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.utm.8402 |
---|---|
record_format |
eprints |
spelling |
my.utm.84022010-09-21T07:46:05Z http://eprints.utm.my/id/eprint/8402/ Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search Ismail, Zuhaimy Irhamah, Irhamah QA Mathematics This study considers a version of the stochastic vehicle routing problem where customer demands are random variables with known probability distribution. A new scheme based on a hybrid GA and Tabu Search heuristic is proposed for this problem under a priori approach with preventive restocking. The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities resulted Science Publications 2008 Article PeerReviewed Ismail, Zuhaimy and Irhamah, Irhamah (2008) Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search. Journal of Mathematics and Statistics, 4 (3). pp. 161-167. ISSN 1549-3644 http://www.scipub.org/fulltext/jms2/jms243161-167.pdf |
institution |
Universiti Teknologi Malaysia |
building |
UTM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Teknologi Malaysia |
content_source |
UTM Institutional Repository |
url_provider |
http://eprints.utm.my/ |
topic |
QA Mathematics |
spellingShingle |
QA Mathematics Ismail, Zuhaimy Irhamah, Irhamah Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
description |
This study considers a version of the stochastic vehicle routing problem where customer demands are random variables with known probability distribution. A new scheme based on a hybrid GA and Tabu Search heuristic is proposed for this problem under a priori approach with preventive restocking. The relative performance of the proposed HGATS is compared to each GA and TS alone, on a set of randomly generated problems following some discrete probability distributions. The problem data are inspired by real case of VRPSD in waste collection. Results from the experiment show the advantages of the proposed algorithm that are its robustness and better solution qualities resulted |
format |
Article |
author |
Ismail, Zuhaimy Irhamah, Irhamah |
author_facet |
Ismail, Zuhaimy Irhamah, Irhamah |
author_sort |
Ismail, Zuhaimy |
title |
Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
title_short |
Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
title_full |
Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
title_fullStr |
Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
title_full_unstemmed |
Solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
title_sort |
solving the vehicle routing problem with stochastic demands via hybrid genetic algorithm-tabu search |
publisher |
Science Publications |
publishDate |
2008 |
url |
http://eprints.utm.my/id/eprint/8402/ http://www.scipub.org/fulltext/jms2/jms243161-167.pdf |
_version_ |
1643644982481911808 |
score |
13.18916 |