Research on Parallel Optimization of Chaotic Ant Colony Algorithm

A Parallel Ant Colony Optimization Algorithm Based on Crossover Operation

Parallel Ant Colony Optimization Algorithm on a Multi-core Processor

This paper proposes parallelization methods of ACO algorithms on a computing platform with a multi-core processor aiming at fast execution to find acceptable solutions. As an ACO algorithm, we use the cunning Ant System and test on several sizes of TSP instances. As the parallelization method, we use agent level parallelization in one colony using Java thread programming. According to the synch...

Ant Colony Optimization Algorithm

Hybrid algorithm is proposed to solve combinatorial optimization problem by using Ant Colony and Genetic programming algorithms. Evolutionary process of Ant Colony Optimization algorithm adapts genetic operations to enhance ant movement towards solution state. The algorithm converges to the optimal final solution, by accumulating the most effective sub-solutions.

A survey on parallel ant colony optimization

Ant Colony Optimization (ACO) is a well-known swarm intelligence method, inspired in the social behavior of ant colonies for solving optimization problems. When facing large and complex problem instances, parallel computing techniques are usually applied to improve the efficiency, allowing ACO algorithms to achieve high quality results in reasonable execution times, even when tackling hard-to-s...

Adaptive Parallel Ant Colony Algorithm

An adaptive parallel ant colony optimization is presented by improving the critical factor influencing the performance of the parallel algorithm. We propose two different strategies for information exchange between processors: selection based on sorting and on difference, which make each processor choose another processor to communicate and update the pheromone adaptively. In order to increase ...