Dynamics of Deprivation Cost in Last Mile Distribution The Integrated Resource Allocation and Vehicle Routing Problem
Abstract
One of the most critical tasks after a natural disaster is to organize and execute
humanitarian relief operations effectively and efficiently while reaching an equitable
outcome. However, due to limited resources in the initial stage of response, it becomes
challenging for logistics planning authorities to target needed individuals. The concerns
would be with providing an unbiased platform to make decisions about equitable
distribution schedules. Therefore, developing an effective and efficient disaster relief plan
that tries to treat individuals as equitable as possible was the main motivation in this
research. For this purpose, this dissertation studied a novel last mile distribution plan in the
initial response phase where the key focus is the preservation of lives. An integrated
vehicle routing and resource allocation problem was investigated and formulated in an
routing-allocation model (RAP). The theoretical foundation of RAP is formulated as an
egalitarian model where resources are to be distributed so as to maximize the welfare of
those in greatest need. The strategic goal is to alleviate human deprivation and suffering by
minimizing the response time in regard to each beneficiary’s needs fulfillment and delivery
delay on the route. Equity is quantified with a min-max objective on a deprivation cost,
which is a non-linear function of deprivation time. The objective function is set to
minimize the maximum deprivation cost of the deliveries so that supplies arrive in a
cyclical manner while all demand sites are treated equitably.