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SUMMARY:Wildfire analytics: optimisation of fuel reduction
DTSTART:20240305T150000
DTEND:20240305T160000
DTSTAMP:20260407T195107Z
UID:7f28bcefdda248df48d7e77f33e6a947a6f0d208e839b72d5dece0db
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Dmytro Matsypura\nAbstract : Wildfires are a common phen
 omenon on most continents. They have occurred for an estimated 60 million 
 years and are part of a regular climatic cycle. Nevertheless\, wildfires r
 epresent a real and continuing problem that can have a significant impact 
 on people\, wildlife and the environment\, especially since their severity
  has been worsening rapidly over the past decade. The intensity and severi
 ty of wildfires can be reduced through fuel reduction activities. The most
  common and effective fuel reduction activity is prescribed burning. We pr
 opose a multi-period optimization framework based on mixed integer program
 ming (MIP) techniques to determine the optimal spatial allocation of presc
 ribed burning activities over a finite planning horizon. \nIn contrast to
  the existing literature\, we model fuel accumulation with a modified Olso
 n’s equation. To capture potential fire spread along with irregular land
 scape connectivity\, we use a graph-theoretical approach that allows us to
  exploit graph connectivity measures as optimization objectives. The resul
 ting mathematical programs can be tackled by general-purpose MIP solvers. 
 Our computational experiments reveal interesting insights and demonstrate 
 the advantages and limitations of the proposed approaches.\n \nBio : Dmyt
 ro Matsypura is an Associate Professor in the Discipline of Business Analy
 tics at the University of Sydney Business School. He received his B.S. and
  M.S. degrees in Information Systems from Kyiv Polytechnic Institute (Ukra
 ine) and a Ph.D. in Management Science from the University of Massachusett
 s Amherst. His current research focuses on applications of convex and comb
 inatorial optimisation in forecasting\, graph theory\, transportation\, an
 d ecology.
LOCATION:ODY 4 03 https://plan.epfl.ch/?room==ODY%204%2003
STATUS:CONFIRMED
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