A hybrid algorithm based on state-adaptive slime mold model and fractional-order ant system for the travelling salesman problem

A hybrid algorithm based on state-adaptive slime mold model and fractional-order ant system for the travelling salesman problem

Abstract The ant colony optimization (ACO) is one efficient approach for solving the travelling salesman problem (TSP). Here, we propose a hybrid algorithm based on state-adaptive slime mold model and fractional-order ant system (SSMFAS) to address the TSP. The state-adaptive slime mold (SM) model w...

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Bibliographic Details
Main Authors: Xiaoling Gong, Ziheng Rong, Jian Wang, Kai Zhang, Shengxiang Yang
Format: Article
Language:English
Published: Springer 2022-12-01
Series:Complex & Intelligent Systems
Subjects:
Ant system (AS)
Slime mold (SM)
Fractional-order calculus
Travelling salesman problem (TSP)
Convergence proof
Online Access:https://doi.org/10.1007/s40747-022-00932-1

Internet

https://doi.org/10.1007/s40747-022-00932-1

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