Abstract
In the inevitable trends of the modern aerial equipment, unmanned aerial vehicle (UAV) is one of the most concerned components to research. This paper presents a saving memory optimization algorithm of Compact artificial bee colony (cABC) for UAVs route planning problem. In the proposed method, route length and danger exposure are modeled mathematically as the objective function, and the compact algorithm concept is implemented to accommodate the route planning situation. In the compact algorithm, actual design variable of solutions search space of artificial bee colony algorithm is replaced with a probabilistic representation of the population. A probabilistic representation random of the collection behavior of bees is inspired to employ for this proposed algorithm. The real population is replaced with the probability vector updated based on single competition. The computational results compared with other algorithms in the literature shows that the proposed method can provide the effective way of using a modest memory for UAV route planning problem.
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Pan, TS., Dao, TK., Pan, JS., Nguyen, TT. (2017). An Unmanned Aerial Vehicle Optimal Route Planning Based on Compact Artificial Bee Colony. In: Pan, JS., Tsai, PW., Huang, HC. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-319-50212-0_43
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DOI: https://doi.org/10.1007/978-3-319-50212-0_43
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