The Effects of Variation on Solving a Combinatorial Optimization Problem in Collaborative Multi-Agent Systems

In collaborative multi-agent systems, the participating agents have to join forces in order to solve a common goal. The necessary coordination is often realized by message exchange. While this might work perfectly in simulated environments, the implementation of such systems in a field application usually reveals some challenging properties: arbitrary communication networks, message delays due to specific communication technologies, or differing processing speeds of the agents. In this contribution we interpret these properties as sources of variation, and analyze four different multi-agent heuristics with respect to these aspects. In this regard, we distinguish synchronous from asynchronous approaches, and draw conclusions for either type. Our work is motivated by the use case of scheduling distributed energy resources within self-organized virtual power plants.