Instances for the problem of pre-positioning emergency supplies

Abstract

Purpose – Despite a growing body of research on the problem of increasing disaster preparedness by pre-positioning relief supplies at strategic locations, there is a lack of a benchmark set of problem instances that hinders thorough hypotheses testing, sensitivity analysis, model validation or solution procedure evaluation. The purpose of this paper is to address this issue by constructing a public library of diverse pre-positioning problem instances. Design/methodology/approach – By carefully manipulating some of the instance parameters, the authors generated 30 case studies that were inspired by four instances collected from the literature that focus on disasters of different type and scale that occurred in different parts of the world. In addition, the authors developed a tool to algorithmically generate arbitrarily many diverse random instances of any size. Findings – For many purposes, the problem library can eliminate or reduce the time-consuming process of data collection, conversion, digitization, calibration and validation, while simultaneously increasing the statistical significance of research results and allowing comparison with different works in the literature. Research limitations/implications – The case studies are inspired by only four disasters, and some of the instance parameters are defined in a reasonable, albeit arbitrary way. The instances are also limited by the underlying problem assumptions. Practical implications – The instances provide a more comprehensive and balanced experimental setting (compared to a single case study) that can be used to study the pre-positioning and related problems, or derive managerial implications that can directly benefit the practitioners. Social implications – The instances can be used to derive practical guidelines that humanitarian workers can use on the ground to better plan their pre-positioning strategies and therefore minimize human suffering. Originality/value – The case studies and the random instance generator are made publicly available to foster further research on the problem of pre-positioning relief supplies and humanitarian logistics in general.

Keywords

• Humanitarian logistics
• Case study
• Pre-positioning emergency supplies
• Random instance