Optimal minimal-contact routing of randomly arriving agents through connected networks

TL;DR

This paper develops an optimization framework for routing agents through connected networks to minimize or eliminate contacts, considering stochastic factors, with applications in industrial and health safety contexts.

Contribution

It introduces two real-time optimization formulations for contact-free routing in networks, accounting for stochastic travel speeds and compliance, applicable to various industries and pandemic scenarios.

Findings

Reduced average contacts in simulated scenarios

Effective real-time route generation for agents

Quantified trade-offs between contact minimization and travel time

Abstract

Collision-free or contact-free routing through connected networks has been actively studied in the industrial automation and manufacturing context. Contact-free routing of personnel through connected networks (e.g., factories, retail warehouses) may also be required in the COVID-19 context. In this context, we present an optimization framework for identifying routes through a connected network that eliminate or minimize contacts between randomly arriving agents needing to visit a subset of nodes in the network in minimal time. We simulate the agent arrival and network traversal process, and introduce stochasticity in travel speeds, node dwell times, and compliance with assigned routes. We present two optimization formulations for generating optimal routes - no-contact and minimal-contact - on a real-time basis for each agent arriving to the network given the route information of other agents already in the network. We generate results for the time-average number of contacts and normalized time spent in the network.