Abstract
The scheduling of processes in a network is a core logistic challenge with a multitude of applications in our complex industrialized world. Often, scheduling decisions are based on incomplete and unreliable information. Here, a simple rule of ’more information, better decisions’ may no longer hold and heuristics balancing global and local information, or centralized and autonomous control, may yield better performance. So far, only anecdotal evidence for the potential benefit of autonomous control in scheduling exists. Here, we explore this hypothesis within a minimal model derived from scheduling principles and the phenomenology of dynamical processes on graphs. In this model, centralized and autonomous control can be represented and quantitatively assessed, performance is well defined and problem complexity can be varied.Our model shows that a balance of centralized and autonomous control can enhance the performance in networks of decision-making entities. The mechanistic insight gained from the model also reveals the limitations of hybrid control setups: We find that communication at a high hierarchy level can give an advantage to centralized control. Counter-intuitively, it arises not from a higher degree of coordination and quicker convergence towards a common solution, but rather from an accelerated sampling of candidate choices leading to a measurable increase in information flow from higher to lower hierarchical levels. Our study allows us to formulate a new view of autonomous control in industrial production and derive a set of suggestions with the potential to enhance performance under realistic conditions of scheduling heuristics of jobs in a production process.
Highlights
Diverse real-world organizational challenges can be mapped onto the abstract problem of scheduling events on a network (Pinedo 2012)
From the viewpoint of production planning and control, variation of the amount of hierarchy in the network is typically considered a suitable way of structurally varying the balance between decentralized and centralized control – with highly hierarchical structures being associated with centralized, global control, while more spread-out, heterarchical structures are associated with decentralized, local control (Trentesaux 2009)
Increasing neighborhood size could allow the transition towards ever more centralized control. In practice such rule-based changes of the control type are not easy to implement: (1) update rules operating on different neighborhood sizes are difficult to compare; (2) in industrial production systems realistic networks typically have a few hundred nodes; in this case, the diameter of the graph is so small that when going from nearest neighbors to nextto-nearest neighbors in a node’s update rule, already a substantial portion of the graph is covered1
Summary
Diverse real-world organizational challenges can be mapped onto the abstract problem of scheduling events on a network (Pinedo 2012). A more subtle effect is that distal information can be systematically wrong or outdated due to the longer transmission time, leading to an increase in erroneous decisions, as they are based on essentially random information. This is fascinating when the deterioration of distal information arises from the decision process itself (i.e. from the updates / decisions occurring at distal system sites), linking the topic of local decisions to the general framework of emergent collective behaviors and self-organization (Moreira et al 2004a; Marr and Hütt 2006; Tang et al 2014)
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