Population Iterative Annealing Algorithm with Improved Inver-over Operator for TSP

DOI

10.2991/msota-16.2016.59How to use a DOI?

Keywords

TSP; population intelligent algorithm; inver-over operator; simulated annealing algorithm; iterative annealing

Abstract

For improving optimizing ability of Inver-over operator in solving TSP, we improved the Inver-over operator and employing annealing skill. First, adopted two strategies to improve Inver-Over operator, one is drawing more optimal edges into the population as earlier mainly through the "2e-switch-1p-shift-opt", and another is avoiding nonfunctional iterations considering the similarity of the population, these improvements increased the converging speed evidently. Second, employed annealing skill in the improved population algorithm, by designing the temperature function with the characteristics of the population, the temperature of the annealing process presented self-adaptive and two-stage decreasing characteristic, the temperature can achieve peak and then decrease periodically, and the peak was decreased gradually. The individuals in the population except the best one can jump present local area with large probability and search in new area. The experiment results showed that the proposed algorithm overcomes GT algorithm in the con-verging speed and final tour obviously.

Copyright

© 2017, 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  - Zhi Yuan
AU  - Yuanping Zhang
PY  - 2016/12
DA  - 2016/12
TI  - Population Iterative Annealing Algorithm with Improved Inver-over Operator for TSP
BT  - Proceedings of 2016 International Conference on Modeling, Simulation and Optimization Technologies and Applications (MSOTA2016)
PB  - Atlantis Press
SP  - 272
EP  - 276
SN  - 2352-538X
UR  - https://doi.org/10.2991/msota-16.2016.59
DO  - 10.2991/msota-16.2016.59
ID  - Yuan2016/12
ER  -