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Sudipta Chowdhury,Mohammad Marufuzzaman,Huseyin Tunc,Linkan Bian,William Bullington 한국CDE학회 2019 Journal of computational design and engineering Vol.6 No.3
This study presents a novel Ant Colony Optimization (ACO) framework to solve a dynamic traveling sales-man problem. To maintain diversity via transferring knowledge to the pheromone trails from previous environments, Adaptive Large Neighborhood Search (ALNS) based immigrant schemes have been devel-oped and compared with existing ACO-based immigrant schemes available in the literature. Numerical results indicate that the proposed immigrant schemes can handle dynamic environments efficiently com-pared to other immigrant-based ACOs. Finally, a real life case study for wildlife surveillance (specifically, deer) by drones has been developed and solved using the proposed algorithm. Results indicate that the drone service capabilities can be significantly impacted when the dynamicity of deer are taken into consideration.