Adaptive Discrete Cuckoo Algorithm Based on Simulated Annealing for Solving TSP

ZHANG Zi-cheng; HAN Wei; MAO Bo

doi:10.3969/j.issn.0372-2112.2018.08.008

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Adaptive Discrete Cuckoo Algorithm Based on Simulated Annealing for Solving TSP

更新时间：2025-07-16

- Adaptive Discrete Cuckoo Algorithm Based on Simulated Annealing for Solving TSP
- Acta Electronica Sinica Vol. 46, Issue 8, Pages: 1849-1857(2018)
- 作者机构：
  
  1. 南京财经大学信息工程学院,江苏,南京,210046
  2. 现代粮食流通与全协同创新中心,江苏,南京,210046
  3. 江苏省粮食大数据挖掘与应用重点实验室,江苏,南京,210046
  4. 南京财经大学信息工程学院,江苏,南京,210046
  5. 现代粮食流通与全协同创新中心,江苏,南京,210046
  6. 江苏省粮食大数据挖掘与应用重点实验室,江苏,南京,210046
- 作者简介：
- 基金信息：
  
  Subject of National Key Technology Research and Development Program Research and Development of Key technologies and Equipment for Agricultural Goods Logistics Anti-Counterfeiting and Traceability (No.2015BAD18B02)
- DOI：10.3969/j.issn.0372-2112.2018.08.008
  CLC： TN92
- Published Online：25 August 2018，
  
  Published：2018
- 稿件说明：
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ZHANG Zi-cheng, HAN Wei, MAO Bo. Adaptive Discrete Cuckoo Algorithm Based on Simulated Annealing for Solving TSP[J]. Acta Electronica Sinica, 2018, 46(8): 1849-1857.
DOI：

ZHANG Zi-cheng, HAN Wei, MAO Bo. Adaptive Discrete Cuckoo Algorithm Based on Simulated Annealing for Solving TSP[J]. Acta Electronica Sinica, 2018, 46(8): 1849-1857. DOI： 10.3969/j.issn.0372-2112.2018.08.008.

摘要

提出了一种基于模拟退火的自适应离散型布谷鸟算法求解旅行商问题.该算法在布谷鸟搜索算法原理的基础上，构造了旅行商问题的路径求解策略.由于算法的局限性，随着算法的调整和迭代次数的增加，容易破坏已形成的路径，从而使得算法通用性不强.针对这一局限性，本文提出了一种自适应局部调整算子和全局随机扰动策略.采用简单的2-opt算子作为局部优化算子加快算法收敛速度，引入模拟退火机制防止算法陷入局部最优.采用标准TSPLIB多组数据进行测试，并与有代表性的优化算法进行结果比较.实验结果证明了该算法在精度和稳定性方面的优势.

Abstract

An adaptive discrete cuckoo algorithm based on simulated annealing is proposed to solve the traveling salesman problem.The proposed algorithm constructs the path solving strategy of traveling salesman problem based on the principle of cuckoo search algorithm.Due to the limitation of algorithm

with the increasing of the number of iterations

it is inclined to destroy the formed paths

which makes algorithm can not be commonly used in variant applications.To overcome this shortcoming

this paper adopt an new strategy which adjust operator locally and disturb parameters randomly.A simple 2-opt operator is used as the local optimization operator to accelerate the convergence rate of the algorithm.The simulated annealing mechanism is introduced to prevent the local optimum in early iterations.The algorithm is tested by the standard TSPLIB multi-group data

comparing with several representative traveling salesman problem algorithm

the experimental results show the advantages of the algorithm in terms of accuracy and stability.

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Ant-Q Algorithm Based on Knowledge Transfer

Chaotic Hybrid Discrete Bat Algorithm for Traveling Salesman Problem

Equilibrium Single Evolution Based Cuckoo Search Algorithm

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