Distributed Key Figure Optimization Approaches for Global Goal Coordination in Multi-agent Systems for Production Control

Performance measurement by means of key performance indicators (KPIs) is a widespread device for communicating qualitative and quantitative business objectives throughout an organization and monitoring their achievement. It seems desirable to also apply this concept to dependably influencing the operational behaviour of distributed agent controlled processes, which have progressively gained in importance in production logistics and control over recent years as compared to centralized control methods. However, planning and scheduling with numeric goal systems at present still poses a challenging task within the field of computational intelligence.In this paper, a framework is presented that enables global coordination of agents in a multi-agent system through user-configurable numeric key performance indicators and associated objectives. A practical approach to distributed control based on periodical mathematical optimization of the defined KPI goal system is described that focuses on how automatic key figure aggregation over changing groups and hierarchies of agents and other business objects can be appropriately managed when proactive modification of these organizational structures, e.g., agents deliberately forming and disbanding groups, is an integral part of the control problem. Five variants of this approach are compared in a case study with a simulated shop floor where incoming manufacturing orders need to be assigned to different machine tools.