Inventory routing for defense: Moving supplies in adversarial and partially observable environments

Michelle Blom, Slava Shekh, Don Gossink, Tim Miller and Adrian R Pearce

The Journal of Defense Modeling and Simulation, 2020, vol. 17, issue 1, 55-81

Abstract: Future defense logistics will be heavily reliant on autonomous vehicles for the transportation of supplies. We consider a dynamic logistics problem in which: multiple supply item types are transported between suppliers and consuming (sink) locations; and autonomous vehicles (road-, sea-, and air-based) make decisions on where to collect and deliver supplies in a decentralized manner. Sink nodes consume dynamically varying demands (whose timing and size are not known a priori). Network arcs, and vehicles, experience failures at times, and for durations, that are not known a priori. These dynamic events are caused by an adversary, seeking to disrupt the network. We design domain-dependent planning algorithms for these vehicles whose primary objective is to minimize the likelihood of stockout events (where insufficient resource is present at a sink to meet demand). Cost minimization is a secondary objective. The performance of these algorithms, across varying scenarios, with and without restrictions on communication between vehicles and network locations, is evaluated using agent-based simulation. We show that stockpiling-based strategies, where quantities of resource are amassed at strategic locations, are most effective on large land-based networks with multiple supply item types, with simpler “shuttling†-based approaches being sufficient otherwise.

Keywords: Defense logistics; autonomous vehicles; dynamic inventory routing; partial observability; agent-based simulation (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1548512918798056 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:joudef:v:17:y:2020:i:1:p:55-81

DOI: 10.1177/1548512918798056

Access Statistics for this article

More articles in The Journal of Defense Modeling and Simulation
Bibliographic data for series maintained by SAGE Publications ().