Combining Agent-Based Approaches and Classical Optimization Techniques

The strengths and weaknesses of agent-based approaches and classical optimization techniques are analyzed and compared. Their appropriateness for dynamic distributed resource allocation is evaluated. We conclude that their properties are complementary and that it seems beneficial to combine the approaches. Some suggestions of hybrid systems are sketched and two of these are implemented and evaluated in a case study and compared to pure agent and optimization-based solutions. The case study concerns production and transportation decisions in a supply chain. In the hybrid systems, optimization was used for improving the agents' decision making capability, i.e. embedded optimization, and for creating a coarse plan used by the agents in order to improve the short term decisions. The results from the case study indicate that it is possible to capitalize both on the agents' ability of being reactive and on the ability of optimization techniques of finding high quality solutions.