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Route Planning Based on Genetic Algorithm

Author

Listed:
  • Lin Li
  • Yuhua Zhang

Abstract

This paper mainly deals with the planning of aviation route and needs to determine the model to find out the shortest path. In this paper, we combine the methods of simulated annealing and genetic algorithm, and obtained the optimal solution method. Firstly, Genetic Algorithm (GA) uses the modified circle algorithm to find some feasible solutions to the approximate initial population, and then transforms them through simulated and crossover operations. This paper also introduces the aircraft fuel consumption model and the cubical smoothing algorithm with five-point approximation to reduce the aircraft fuel consumption and parts loss. The simulation results show that the accuracy of the route planning based on genetic algorithm is higher, while consumes less fuel and takes less sharp turns.

Suggested Citation

  • Lin Li & Yuhua Zhang, 2018. "Route Planning Based on Genetic Algorithm," Journal of Mathematics Research, Canadian Center of Science and Education, vol. 10(2), pages 122-128, April.
    • Handle: RePEc:ibn:jmrjnl:v:10:y:2018:i:2:p:122
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    Citations

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    Cited by:

    1. Stenfors, Alexis & Susai, Masayuki, 2021. "Spoofing and pinging in foreign exchange markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 70(C).
    2. Stenfors, Alexis & Susai, Masayuki, 2019. "Liquidity withdrawal in the FX spot market: A cross-country study using high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 36-57.

    More about this item

    Keywords

    route planning; modified circle algorithm; genetic algorithm;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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