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SCIENCE CHINA Information Sciences, Volume 61, Issue 12: 129103(2018) https://doi.org/10.1007/s11432-017-9310-5

Aircraft conflict resolution method based on hybrid ant colony optimization and artificial potential field

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  • ReceivedSep 5, 2017
  • AcceptedDec 14, 2017
  • PublishedNov 15, 2018

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant No. U1533119) and State Key Program of National Natural Science Foundation of China (Grant No. 71731001).


Supplement

Appendices A–G.


References

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    Algorithm 1 Procedure of improved hybrid algorithm

    Input:

    The starting points and destinations of the aircraft.

    Output: (refer to Appendix D)

    (1) CL: computational load;

    (2) F: feasibility;

    (3) SE: system efficiency;

    (4) CP: conflict probability.

    Step 1. Initialize the ant colony (refer to Appendix C).

    Step 2. Get authority ant using artificial potential field.

    (1) Set aircraft number;

    (2) Calculate the flight path of an aircraft by function B(6) in Appendix B;

    (3) Adjust the path and encode it as the authority ant's path.

    Step 3. Generate the authority ant colony.

    Copy authority ant's path Ps times.

    Step 4. Whether satisfy the conditions?

    (1) Satisfy: Output optimization results: CL, F, SE and CP;

    (2) Not satisfy: go to step 5.

    Step 5. Whether satisfy the conditions?

    The ants choose the path by C(1) in Appendix C.

    Step 6. Whether satisfy the conditions?

    (1) Update the pheromone using C(2) in Appendix C;

    (2) Return to step 4.

  •   

    Algorithm 1 Procedure of improved hybrid algorithm

    Input:

    The starting points and destinations of the aircraft.

    Output: (refer to Appendix D)

    (1) CL: computational load;

    (2) F: feasibility;

    (3) SE: system efficiency;

    (4) CP: conflict probability.

    Step 1. Initialize the ant colony (refer to Appendix C).

    Step 2. Get authority ant using artificial potential field.

    (1) Set aircraft number;

    (2) Calculate the flight path of an aircraft by function B(6) in Appendix B;

    (3) Adjust the path and encode it as the authority ant's path.

    Step 3. Generate the authority ant colony.

    Copy authority ant's path Ps times.

    Step 4. Whether satisfy the conditions?

    (1) Satisfy: Output optimization results: CL, F, SE and CP;

    (2) Not satisfy: go to step 5.

    Step 5. Whether satisfy the conditions?

    The ants choose the path by C(1) in Appendix C.

    Step 6. Whether satisfy the conditions?

    (1) Update the pheromone using C(2) in Appendix C;

    (2) Return to step 4.

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