Application of Multi-core Parallel Programming to a Combination of Ant Colony Optimization and Genetic Algorithm

TL;DR

This paper explores parallelizing a combined Ant Colony and Genetic Algorithm for the Traveling Salesman Problem using multi-core systems and OpenMP to significantly reduce computational time.

Contribution

It introduces a parallel implementation of a hybrid Ant Colony and Genetic Algorithm specifically optimized for multi-core architectures.

Findings

Parallel implementation reduces computational time substantially.

OpenMP effectively enables multi-core parallelization.

Hybrid algorithm maintains solution quality with improved efficiency.

Abstract

This Paper will deal with a combination of Ant Colony and Genetic Programming Algorithm to optimize Travelling Salesmen problem (NP-Hard). However, the complexity of the algorithm requires considerable computational time and resources. Parallel implementation can reduce the computational time. In this paper, emphasis in the parallelizing section is given to Multi-core architecture and Multi-Processor Systems which is developed and used almost everywhere today and hence, multi-core parallelization to the combination of algorithm is achieved by OpenMP library by Intel Corporation.