Fire risk management through asset protection routing; optimisation enhanced with machine learning

Event details

This event will discuss wildfire risk management by asset protection strategy through operations research with a focus on the Australia bush fire event.

Abstract

In this presentation, Australia Bush fire event is considered and the asset protection is considered as a strategy for managing risk.

A two-stage stochastic mathematical model is developed for the asset protection routing problem under a wildfire with the aim of reducing the negative impact of a wildfire. Some parameters, such as travel and service times, obtaining profit by protecting an asset, and upper bounds of time windows, are considered as stochastic parameters. An artificial neural network is employed to extract possible scenarios according to previous actual wildfire events. Matheuristic algorithms are proposed to solve the problem in a reasonable time. The numerical analysis are investigated to show the efficiency of proposed algorithms.

Biography

Mahdi has over 17 years of academic experience, with a particular interest in operations and supply chain management, operations research, transportation planning, decision making, and heuristic algorithms. Previously, he was an Associate Head of School for Research in the SSL. He was a professor of Industrial Engineering at Shahed University in Tehran before joining CU. He has been a visiting researcher at LSE and RMIT University in Australia. Mahdi has been involved in UKRI funded projects. He has an H-index of 22 (Scopus) and is an editorial advisory board member of Transportation Research : E (ABS 3*) and an active reviewer for reputable academic journals.

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