The aim of this article is to further discuss the enhanced negative feedback mechanism proposed in (Ye et al., 2017), combined with the idea of pseudo-random ...
Jul 6, 2018 · By introducing an improved negative feedback mechanism, literature [8] improves the convergence accuracy of solving TSP. However, the literature ...
Jan 11, 2024 · Aiming at the problem that the ant colony optimization algorithm with improved negative feedback mechanism is easy to fall into the local ...
Aiming at the problem that the ant colony optimization algorithm with improved negative feedback mechanism is easy to fall into the local optimum when ...
J. Li et al. optimized the negative feedback mechanism, simultaneously updated the pheromone concentration on the worst and optimal path and enhanced the weight ...
A Pseudo-dynamic Search Ant Colony Optimization Algorithm with Improved Negative Feedback Mechanism to Solve TSP. Jun Li, Yuan Xia, Bo Li, Zhigao Zeng.
Based on experiments adopting TSPLIB data sets, the results demonstrate the improved algorithm improves the convergence accuracy by at least 1.26% and increases ...
Missing: TSP. | Show results with:TSP.
Li, Z. G. Zeng, A pseudo-dynamic search ant colony optimization algorithm with improved negative feedback mechanism, Cognit. Syst. Res., 62 (2020), 1–9 ...
People also ask
What is the ant colony optimization algorithm?
How does the ACO algorithm work?
What are the disadvantages of ant colony optimization?
What is ant colony optimization algorithm for robot path planning?
摘要. Aiming at the problem that the ant colony optimization algorithm with improved negative feedback mechanism is easy to.
This study presents a novel Ant Colony Optimization (ACO) framework to solve a dynamic traveling salesman problem. To maintain diversity via transferring ...