Special Issue on Artificial Intelligence in Future Disaster Operations Management

Published 01 October, 2020

Over the past few decades, there has been a steady rise in the number, scale and intensity of natural and human-made disasters including pandemics, wildfires, earthquakes, storms and major floods. These have had significant short and long-term impacts on the societies, economies and built environments. Hundreds of thousands of deaths and billions of dollars of economic loss highlight the importance of effective Disaster Operations Management (DOM) for reducing the destruction impacts and improving the response to such events. Although disaster risk management plans and strategies have evolved in recent years, there are still many challenges that need to be addressed. Due to climate change, the scale and regularity of extreme weather events have been increasing, and it is possible that these events will occur in new areas that have never previously experienced such risks. In addition, recently, the COVID-19 pandemic showed that still many countries across the world are vulnerable to pandemics. In these situations, conventional disaster operations management strategies often fail in immediate action.

Nowadays, Artificial intelligence (AI) is making cities smart in various ways and disaster operations management strategies and plans should also build on AI technologies. AI literature reports on computer aided systems capable of planning operations during disasters. Computer aided methods can analyse problems accurately and give managers and policy makers a better understanding of issues in order to help them to make decisions. AI-based techniques have been applied successfully in solving a wide range of intractable problems and are frequently being used to improve decision making. However, research in applying AI to disaster operations management area is scarce and has not been conducted when responding to emerging challenges such as pandemics, floods, earthquakes and storms.

Topics covered:

  • Supply chain disaster
  • Disaster risk and operations management
  • Supply chain mitigation
  • Supply chain resiliency
  • Reverse logistics and closed-loop supply chains under uncertainty
  • Sustainable supply chains under uncertainty
  • Industry 4.0 and disaster risk reduction
  • Home healthcare logistics under uncertainty
  • Production and flexible manufacturing under uncertainty
  • Machine learning techniques for simulating the destructive effects of natural disaster in industries
  • Simulation of supply chains after disaster events
  • Application of heuristics and metaheuristics in improving DOM
  • Application of big data in improving DOM
  • Waste management with disaster events

Important Deadlines: 

Submission deadline: 31 May 2021

Submission Instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online, please select VSI: AI in the future Disaster Operations Management.

Guest Editors:

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