Project schedule compression for the efficient restoration of interdependent infrastructure systems

The timely restoration of infrastructure networks is critical for society's functionality and wellbeing. However, it is also a substantially challenging task due to the various logistic and resource restrictions from time to budget and work crew availability. Restoration of infrastructure networks is a time-sensitive task as even a slight delay might cause inconvenience or worse to the community for an extended period. As such, diverse models have centered on determining optimal recovery sequences so that recovery time is minimized. However, in some circumstances, given the importance of a timely recovery, even optimal sequences may not result in a quick enough restoration. To address this problem, this paper proposes a multi-objective model for enhanced restoration based on a mixed integer linear programming model that determines optimal job sequencing and crew assignment for a system of interdependent infrastructure networks, while determining key areas for crashing schedule compression, where additional resources would help expedite the full restoration. The implications of project crashing are represented by a cost benefit analysis for a set of solutions enabling the decision maker to study the tradeoffs between restoration duration and restoration cost. The proposed model is applied to a system of interdependent water, power, and gas networks in Shelby County, TN, USA.

Automated summary

The timely restoration of infrastructure networks is critical for society's functionality and wellbeing. This paper proposes a multi-objective model for enhanced restoration by determining optimal job sequencing, crew assignment, and project crashing to expedite the recovery of interdependent infrastructure networks.