A Model for Prepositioning Emergency Relief Items Before a Typhoon with an Uncertain Trajectory

Abstract

Problem definition: We study the problem faced by the Philippine Department of Social Welfare (DSWD) in prepositioning relief items before landfall of an oncoming typhoon whose future outcome (trajectory and wind speed) is uncertain. Academic/practical relevance: The importance of prepositioning was a hard lesson learned from Super Typhoon Haiyan that devastated the Philippines in 2013, when many affected by the typhoon did not have immediate access to food and water. In a typhoon-prone country, it is important to build resilience through an effective prepositioning model. Methodology: By engaging with DSWD, we developed a practically relevant stochastic prepositioning model. The probability models of municipality-level demand and of supply damage are both dependent on the typhoon outcome. A linear mixed effects model is used to estimate the dependence of demand on the typhoon outcome using a large data set that includes the municipality-level impact of West Pacific typhoons during 2008–2019. The model has two objectives motivated from the practical realities of the Philippine network: prioritizing regions with high demand and prepositioning in all affected regions proportional to their total demand. Results: We find that the choice of the demand model significantly impacts the distributed relief items in the Philippine setting where it is challenging to adjust region-level supply after a typhoon. By using the historical data on past typhoons, we show that in this setting, our stochastic demand model provides the best distribution to date of any existing demand models. Managerial implications: There currently exists a gap between theory and practice in the management of relief inventories. We contribute toward bridging this gap by engaging with DSWD to develop a practically relevant relief distribution model. Our work is an effective example of collaboration with government and nongovernment agencies in developing a relief distribution model.

Dynamic Inventory Relocation in Disaster Relief

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The Allocation Method for Personal Protective Equipment in the Emerging Infectious Disease Environment

“…Cao et al ( 30 ) address a dynamic multi-time-period relief distribution model considering supplies uncertainty, hierarchal decision levels and conflicting objectives. Uichanco ( 31 ) develops an integrated stochastic prepositioning model in which the probabilities of demand and supply damage are both dependent on the event outcome.…”

“…In some recent research, the criteria are deepened in detail to the operational level. For instance, Zhou et al ( 47 ) tackle two objectives involving minimizing the unmet demand and minimizing the risk of choosing the damaged road for dynamic emergency resource scheduling problems, Cao et al ( 13 ) pursue simultaneously the maximization of the victims' satisfaction and minimization of the deviation on satisfaction in humanitarian relief distribution, Uichanco ( 31 ) coordinates two objectives involving minimizing the unmet demand and minimizing the unmet proportion of demand for prepositioning humanitarian relief items, Mohammadi et al ( 32 ) consider three objectives where the first objective minimizes the total logistics costs and the third one minimizes the variation between upper and lower bounds of transportation cost. According to incomplete statistical survey involving the recent three-year studies on humanitarian relief logistics optimization, the timeliness (e.g.…”

“…Regarding the methodologies for multi-objective optimization, the Pareto front is worth exploring by some popular methods, such as ε-constrained method ( 31 , 48 ), augmented ε-constrained method ( 10 ) and fuzzy goal constraint approach ( 29 ). When facing large-scale numerical examples, the solution approaches, developing two main streams which include either exact approach and the heuristics, have been widely examined.…”

Impact of Incorporating Returns into Pre‐Disaster Deployments for Rapid‐Onset Predictable Disasters

“…Local purchasing is important to help rebuild local economies and reduce shipping costs; however, many complexities exist if local supplies/suppliers are damaged during the disaster. Uichanco (2016) used a two‐stage robust optimization approach to pre‐position emergency items in anticipation of typhoons in the Philippines. More recently, Balcik et al.…”