Ant colony optimization using two-dimensional pheromone for single-objective transport problems
Grażyna Starzec, Mateusz Starzec, Leszek Rutkowski, Marek Kisiel‐Dorohinicki, Aleksander Byrski
Abstract
One of the acclaimed algorithms that is used to solve combinatorial graph problems is ant colony optimization (ACO). In this article, we focus on a novel extended model of the pheromone that is responsible for storing collective knowledge. The presented two-dimensional pheromone is able to accommodate more information that is extracted from feasible solutions that can be used to improve the search of a solution space. The idea is positively evaluated on TSP and VRP problems, achieving better results as compared to the original algorithm. Since it is a universal concept, it can be applied to any single-objective problem that is solvable by ACO .
Topics & Concepts
PheromoneAnt colony optimization algorithmsComputer scienceANTMathematical optimizationArtificial intelligenceMathematicsBiologyEcologyComputer networkMetaheuristic Optimization Algorithms ResearchVehicle Routing Optimization MethodsAdvanced Multi-Objective Optimization Algorithms