%0 Conference Paper
%A Vu, Duc Quang
%A Nguyen, Van Truong
%A Hoang, Xuan-Huan
%B RIVF 2016
%D 2016
%F SisLab:2369
%T An Improved Artificial Immune Network For Solving Construction Site Layout Optimization
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2369/
%X 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.