Abstract
In this paper, Ant Colony Optimization algorithm is updated with multiple rules to solve the Time-limited tour planning problem. The precision of entertaining time in each sight can significantly increase the time complexity of an algorithm. With tourist attractions opening hour varies from one another, the shortest path will no longer suit the maximum entertaining time. In order to obtain the comprehensive optimal result of both travel time and travel length, the problem is divided into two major steps. The idea of crossover in Genetic Algorithm is introduced here to jumping out of the local loop of solution. Then, the local optimization of time planning is carried out for reducing the time complexity. Time optimizing values are then embedded into an overall travel distance optimization algorithm to acquire final results. By using the method of traversal, the results are verified which are identical to the traversal answer. To test our model, take Pan An Lake scenic spot, Xuzhou, China as an example to give specific results.
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Liu, H., Yu, Z., Zhang, W., Ma, Z. (2020). Time-Limited Tour Planning Based on Ant Colony Optimization Algorithm. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_135
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DOI: https://doi.org/10.1007/978-981-15-1468-5_135
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