The Maximum and Minimum Ant Colony Optimization Waking Strategy Based on Multi-Principle and Reprocessing

  • Wang PengchengEmail author
  • Lin Tao
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 812)


The sensor’s waking strategy is critical to the sensor network. The basic mathematical model of waking strategy is TSP problem. Some typical intelligent algorithms for TSP problem model include ant colony algorithm, genetic algorithm and so on. On the basis of the maximum and minimum ant colony algorithm, this paper improves the following disadvantages: According to the principle of choosing the city based on the pheromone principle, the non-contract principle is added, The principle of city selection and make it in the process of selecting the city, the priority to follow the principle of non-contract; in a single path after the help of the enumeration algorithm with the special advantages, refer to the enumeration algorithm part of the results of the re-processing of the path, The path can cover the search space. The improved algorithm avoids the occurrence of stagnation to a certain extent, weakening the blindness of search. The possibility of the results is increased by 25%, single results of the calculation time is reduced by 89.79%.


Maximum and minimum ant colony algorithm Optimization algorithm Enumeration algorithm Traveling salesman problem Intelligent algorithm Waking strategy 


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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.School of Computer Science and SoftwareHebei University of TechnologyTianjinChina

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