eprintid: 2369
rev_number: 7
eprint_status: archive
userid: 243
dir: disk0/00/00/23/69
datestamp: 2016-12-29 08:26:40
lastmod: 2016-12-29 08:26:40
status_changed: 2016-12-29 08:26:40
type: conference_item
metadata_visibility: show
creators_name: Vu, Duc Quang
creators_name: Nguyen, Van Truong
creators_name: Hoang, Xuan-Huan
creators_id: huanhx@vnu.edu.vn
title: An Improved Artificial Immune Network For Solving Construction Site Layout Optimization
ispublished: pub
subjects: IT
divisions: fac_fit
abstract: Nature-inspired algorithms are often used to find optimal solutions for many combinatorial problems. An immune inspired algorithm, opt-aiNet algorithm, is well known for func- tion optimization. In this paper, we develop a combination of local search with opt-aiNet, called lopt-aiNet, to solve construction site layout (CSL) problem. The effectiveness of the proposed algorithm is investigated through experiments on some datasets taken from the state-of-art and a randomly created dataset. Ex- perimental results show that the lopt-aiNet can produce optimal transportation cost with lower run time compared to the site layouts generated by metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and aiNet.
date: 2016
full_text_status: public
pres_type: paper
event_title: RIVF 2016
event_type: conference
refereed: TRUE
citation:   Vu, Duc Quang and Nguyen, Van Truong and Hoang, Xuan-Huan  (2016) An Improved Artificial Immune Network For Solving Construction Site Layout Optimization.  In: RIVF 2016.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2369/1/QuangRIVF.pdf