Benchmarking a fast, satisficing vehicle routing algorithm for public health emergency planning and response: "Good Enough for Jazz"

PeerJ Comput Sci. 2023 Sep 1:9:e1541. doi: 10.7717/peerj-cs.1541. eCollection 2023.

Abstract

Due to situational fluidity and intrinsic uncertainty of emergency response, there needs to be a fast vehicle routing algorithm that meets the constraints of the situation, thus the receiving-staging-storing-distributing (RSSD) algorithm was developed. Benchmarking the quality of this satisficing algorithm is important to understand the consequences of not engaging with the NP-Hard task of vehicle routing problem. This benchmarking will inform whether the RSSD algorithm is producing acceptable and consistent solutions to be used in decision support systems for emergency response planning. We devise metrics in the domain space of emergency planning, response, and medical countermeasure dispensing in order to assess the quality of RSSD solutions. We conduct experiments and perform statistical analyses to assess the quality of the RSSD algorithm's solutions compared to the best known solutions for selected capacitated vehicle routing problem (CVRP) benchmark instances. The results of these experiments indicate that even though the RSSD algorithm does not engage with finding the optimal route solutions, it behaves in a consistent manner to the best known solutions across a range of instances and attributes.

Keywords: Benchmarking; Experimental analysis of algorithms; Medical counter measure distribution; Routing; Satisficing computational methods; VRP in emergency planning and response.

Grants and funding

The authors received no funding for this work.