Managing combinatorial optimization problems by means of evolutionary computation and multi-agent system

Resumen

The necessity for solving a combinatorial optimization problem is very common. Evolutionary/genetic program could be used to deal with such situations. Unfortunately, depending on the complexity of the problem, high computational capabilities are required, primarily in those cases in which measuring the quality of a potential solution is very demanding. However, advances in Distributed Artificial Intelligence (DAI), Multi-Agent Systems (MAS) to be more specific, could help users to deal with this situation by parallelizing the evolutionary program aiming to distribute the computational capabilities required. This paper presents an inter-agent MAS protocol for parallelizing an evolutionary program aiming to reduce the communications requirements necessary as well as allowing a response within a reasonable period of time.