Agent-Based Generative Simulation of an Intelligent Distributed Scheduling World with Netlogo

Abstract

Unplanned disruptive events and disturbances such as arrivals of rush orders or machine breakdowns must bemanaged locally to avoid propagating the effects along the value chain. To overcome the traditional separationbetween task scheduling and manufacturing execution systems the novel idea of emergent synthesis/control ofschedules for better handling the dynamics at the shop-floor is proposed. A new interaction mechanism forsimultaneous distributed scheduling and execution control is evaluated using a generative simulation model inNetlogo. The interaction mechanism has been designed around the concept of order and resource agents acting asautonomic managers within the artificial society of a dynamic Gantt world. The advantages of generative modellingin agent-based simulation are discussed to emphasize how difficult to predict emerging behaviours and bottom-upmacroscopic dynamics in a manufacturing case study can be addressed by proper design of agent interactions.Results obtained for different abnormal scenarios are presented to highlight the benefits of simulating artificialsocieties of intelligent agents.