A two stage stochastic programming for asset protection routing and a solution algorithm based on the Progressive Hedging algorithm

• Published in: Omega (Oxford) Vol. 104; p. 102480
• Main Authors: Bashiri, Mahdi, Nikzad, Erfaneh, Eberhard, Andrew, Hearne, John, Oliveira, Fabricio
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2021
• Subjects: Asset protection; Frank–Wolfe Progressive Hedging method; Location routing problem; Stochastic programming; Wildfires; Wildfires; Asset protection; Frank–Wolfe Progressive Hedging method; Location routing problem; Stochastic programming
• ISSN: 0305-0483; 1873-5274; 1873-5274
• DOI: 10.1016/j.omega.2021.102480

•Proposing an asset protection routing problem by considering the effect of real factors like temperature, rainfall, etc.•Providing managerial insights on the impacts of considering uncertainties to protect assets properly.•Using a combination of the Progressive Hedging and Frank and Wolf algorithms to find a tight lower bound for model.•Proposing a scenario generation scheme to generate scenarios of uncertain parameters based on a real data in a Bushfire case.•Presenting computational analysis to examine the efficiency of the proposed model under different values of parameters. In this paper, a two-stage stochastic programming model is developed for the asset protection routing problem (APRP) to be employed in anticipation of an escaped wildfire. In this model, strategic and tactical decisions are considered in a two-stage setting. The locations of protection depots are determined, taking into account the routing decisions under different possible scenarios. To solve the proposed model, the Frank–Wolfe Progressive Hedging decomposition approach is employed. A realistic case study set in south Hobart, Tasmania, is considered. In this study, the scenarios for uncertain parameters are generated based on real data, considering different sources of uncertainties such as wind direction and speed and total monthly rainfall. Computational experiments have been conducted to demonstrate the solution algorithm’s efficiency in solving the asset protection routing problem with a two-stage stochastic framework. The numerical results suggest that more assets with higher values can be protected by considering the proposed two-stage stochastic programming model. The value of the approach is particularly significant where resources are limited, and uncertainty levels are high. Moreover, the model and solution procedure can be applied to other disaster situations in which protection activities occur.