A new approach in dynamic traveling salesman problem: a hybrid of ant colony optimization and descending gradient
This is an incremental improvement for researchers and practitioners in optimization algorithms, specifically for dynamic routing problems.
The authors tackled the dynamic traveling salesman problem by proposing a hybrid method combining Ant Colony Optimization and gradient descent, which improved route optimization compared to previous methods.
Nowadays swarm intelligence-based algorithms are being used widely to optimize the dynamic traveling salesman problem (DTSP). In this paper, we have used mixed method of Ant Colony Optimization (AOC)and gradient descent to optimize DTSP which differs with ACO algorithm in evaporation rate and innovative data. This approach prevents premature convergence and scape from local optimum spots and also makes it possible to find better solutions for algorithm. In this paper, we are going to offer gradient descent and ACO algorithm which in comparison to some former methods it shows that algorithm has significantly improved routes optimization.