NENov 12, 2014
Using Ants as a Genetic Crossover Operator in GLS to Solve STSP
arXiv:1411.3277v19 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental improvement for optimization researchers focusing on TSP variants.
The paper tackled the Symmetric Traveling Salesman Problem by proposing a Genetic Local Search algorithm that uses ants from Ant Colony Algorithm as a novel crossover operator, achieving unspecified results without concrete numbers.
Ant Colony Algorithm (ACA) and Genetic Local Search (GLS) are two optimization algorithms that have been successfully applied to the Traveling Salesman Problem (TSP). In this paper we define new crossover operator then redefine ACAs ants as operate according to defined crossover operator then put forward our GLS that uses these ants to solve Symmetric TSP (STSP) instances.