The multiple shortest path problem with path deconfliction

Abstract

To address the increasingly relevant challenge of routing autonomous agents within contested environments, this research formulates and examines the Multiple Shortest Path Problem with Path Deconfliction (MSPP-PD) to balance agent routing efficiency with group vulnerability. Within the general model formulation, multiple agents are routed between respective source and terminus nodes while minimizing both the total distance travelled and a measure of path conflict, where path conflict occurs for any instance of more than one agent traversing an arc and/or node. Within this modeling structure, this research presents and inspects a set of alternative, conceptually-motivated penalty metrics to inhibit path conflict between agents. Illustrative testing demonstrates the distinguishability of different MSPP-PD variants as they relate to optimal agent routing solutions, as well as the non-dominated solutions attainable via different relative priorities over the objective functions. Subsequent empirical testing over a set of synthetic instances demonstrates the effect of different penalty function metrics on both optimal solutions and the computational effort required to identify them. Concluding the work are recommendations about the utility of the MSPP-PD model variants, both individually and collectively.