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An Improved Artificial Immune Network For Solving Construction Site Layout Optimization

Duc Quang Vu and Van Truong Nguyen and Xuan-Huan Hoang (2016) An Improved Artificial Immune Network For Solving Construction Site Layout Optimization. In: RIVF 2016.

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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.

Item Type:Conference or Workshop Item (Paper)
Subjects:Information Technology (IT)
Divisions:Faculty of Information Technology (FIT)
ID Code:2369
Deposited By: Dr Ngoc Thang Bui
Deposited On:29 Dec 2016 08:26
Last Modified:29 Dec 2016 08:26

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