Agent-Based Meta-Heuristic Approach to Discrete Optimization

The paper presents an idea of agent-based meta-heuristic integrating a computational optimization system (evolutionary multi-agent system) with ant colony optimization technique. In the proposed model, chosen parameters of ant colonies may be encoded as genotypes and subjected to evolution process carried out by agents. The goal of the whole system is to search for the best solution of the discrete optimization problem based on the results of the ant colonies run using different parameters. The proposed concept forms a base for further research on bringing different interactions known in ant-colony optimization to the inter-agent level. The considerations are illustrated with preliminary experimental results obtained for parallel ant system solving quadratic assignment problem.