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- W2564449274 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 function 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. Experimental 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." @default.
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- W2564449274 date "2016-11-01" @default.
- W2564449274 modified "2023-09-24" @default.
- W2564449274 title "An improved artificial immune network for solving construction site layout optimization" @default.
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- W2564449274 doi "https://doi.org/10.1109/rivf.2016.7800266" @default.
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