@article{Shahparvari_Chhetri_Abareshi_Abbasi_2015, place={Australia}, title={Multi-Objective Decision Analytics for Short-Notice Bushfire Evacuation: An Australian Case Study}, volume={19}, url={https://journal.acs.org.au/index.php/ajis/article/view/1181}, DOI={10.3127/ajis.v19i0.1181}, abstractNote={This paper develops a multi-objective optimisation model to compute resource allocation,shelter assignment and routing options to evacuate late evacuees from affected areas to shelters.Three bushfire scenarios are analysed to incorporate constraints of restricted time-window and potential road disruptions.Capacity and number of rescue vehicles and shelters are other constraints that are identical in all scenarios.The proposed mathematical model is solved by ?-constraint approach.Objective functions are simultaneously optimised to maximise the total number of evacuees and assigned rescue vehicles and shelters.We argue that this model provides a scenario-based decision-making platform to aid minimise resource utilisation and maximise coverage of late evacuees.}, journal={Australasian Journal of Information Systems}, author={Shahparvari, Shahrooz and Chhetri, Prem and Abareshi, Ahmad and Abbasi, Babak}, year={2015}, month={Sep.} }