Optimization Approaches and Information Systems for Integrated Humanitarian Logistics

Giuseppe Timperio

Publications of Darmstadt Technical University, Institute for Business Studies (BWL) from Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL)

Abstract: Progressive urbanization of disaster-prone areas and the escalating impacts of climate change are contributing to a sharp increase in complex natural disasters. Amidst shrinking financial resources for disaster response, the need for improving decision-making in humanitarian logistics and supply chain management, the backbone of disaster relief absorbing between 60 and 80% of relief budgets, is imperative. Central to many challenges inhibiting effective and efficient provision of relief assistance is that most humanitarian organizations operate in silos. As a result, disaster response operations often experience suboptimal response times, over- or under-supply of necessary items, and higher-than-expected costs. In addressing these compelling challenges, the traditional organization- and execution-centric approach to humanitarian logistics is no longer sufficient. The increased complexity of humanitarian operations calls for a multidisciplinary research effort, with greater attention to ecosystem-aware, beneficiary-centric supply chain networks, with simultaneous attention to both planning and execution of humanitarian operations in consideration of the highly unpredictable and volatile environment relief assistance is delivered in. Despite the multifaceted nature of these challenges, rigorous, practice-focused research-based frameworks remain lacking in the existing body of knowledge. To fill this gap, this dissertation project presents a series of progressive multi-method decision support frameworks that integrate analytical and dynamic simulation approaches and rigorously validate them through realistic use cases, aspiring to address the multiple dimensions of the problem statement. By architecting modular frameworks that encompass models, data, knowledge, and technology, this dissertation goes beyond the use of standalone methods, striving to provide adaptable, practice-based approaches suitable for diverse disaster contexts and geographies.

Date: 2024-09-13
New Economics Papers: this item is included in nep-env and nep-ipr
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