Ocean Fishing Fleet Scheduling Path Optimization Model Research Based On Improved Ant Colony Algorithm

DOI

10.2991/icsmim-15.2016.67How to use a DOI?

Keywords

Ocean fishing fleet, Scheduling problem, Mathematical model, Improved ant colony algorithm

Abstract

Ocean fishing fleet scheduling is a new problem. It produces with the development of pelagic fishery and fleet size enlargement in recent years. At present, ocean fishing fleet scheduling is relying on operator's experience for artificial scheduling. Just rely on the operator's experience scheduling fishing boats not only low efficiency but also lack of scientific nature. On the basis of the analysis of the characteristics of the problem, a routing model of ocean going vessels fleet scheduling is established and using the randomness and certainty transfer strategy and combining the 2-opt optimization method of ACA to analyze and solve the model. The simulation experimental results show that on ocean fishing fleet scheduling path problem, improved ant colony algorithm can make the algorithm fast convergence and path shorter scheduling scheme can be obtained quickly. It can effectively solve the problem of ocean fishing fleet scheduling path.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jia-Lin Li
AU  - Li-Juan Yu
AU  - Cheng-Ming Chen
PY  - 2016/01
DA  - 2016/01
TI  - Ocean Fishing Fleet Scheduling Path Optimization Model Research Based On Improved Ant Colony Algorithm
BT  - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
PB  - Atlantis Press
SP  - 358
EP  - 363
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsmim-15.2016.67
DO  - 10.2991/icsmim-15.2016.67
ID  - Li2016/01
ER  -