Optimization Model Based on Reachability Guarantee for Emergency Facility Location and Link Reinforcement

Abstract

The reasonable location of emergency facilities plays an important role in both predisaster service and postdisaster relief. Moreover, damage to the transportation network often affects the accessibility of demand points, which can seriously hamper timely rescue operations. Reasonable location of emergency facilities and reinforcement of fragile roads are two important strategies to improve the reachability of demand points. In this paper, we proposed a biobjective optimization model to determine locations of emergency facilities and links to be reinforced given a limited budget. Each demand point is allocated a primary facility and a backup facility, the former can provides normal service, and the latter is prepared for postdisaster relief. One goal of the model is to minimize the operating cost of normal services, and another goal is to maximize the reachability guarantee of demand points. The novelty and contribution of this paper are that we defined the reachability by introducing damage tolerance instead of link failure probability. Based on this, we defined the reachability guarantee to deal with the worst scenario of disasters. By embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, the locations of emergency facilities and links to be reinforced can be determined simultaneously. The methodology is applied to a simplified Sioux Falls transportation network. Results such as the trade-off curve of two goals, budget efficiency, and the effect of reinforcement demonstrated the effectiveness of the model.

Optimized Location and Assignment of Emergency Response Assets in Offshore Energy Basins

“…Notably, the model's results, derived from matrix encoding, accompanied by associated evolutionary operators and coupled with Pareto-based multi-objective evolutionary algorithms, showed the potential for effective location decisions based on decision criteria assigned by stakeholders (Men et al, 2020). Yu and Liu (2020), embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, evaluated the location of emergency assets while accounting for damage tolerances in lieu of link failure. In essence, the model optimized the location of emergency assets assuming some links, as part of the deployment of such assets, would first require restoration (Yu & Liu, 2020).Overall, the bi-objective optimization model assessed combinations of primary depots and secondary depots for demand points, which minimized network costs and enhanced reachability, respectively.…”

“…Yu and Liu (2020), embedding the max-flow problem of the reachability guarantee into the emergency facility location problem, evaluated the location of emergency assets while accounting for damage tolerances in lieu of link failure. In essence, the model optimized the location of emergency assets assuming some links, as part of the deployment of such assets, would first require restoration (Yu & Liu, 2020).Overall, the bi-objective optimization model assessed combinations of primary depots and secondary depots for demand points, which minimized network costs and enhanced reachability, respectively. Yu (2021) incorporated randomness and uncertainty within two stages of the pre-disaster location and storage model.…”

Road Rescue Demand Prediction for the Improvement of Traffic System Resilience

“…In the previous research studies, the studies about rescue in emergency mainly include rescue methodology [16], rescue architecture [17,18], accessibility of emergency service [19], emergency resource allocation [20][21][22][23][24][25][26][27][28], the determination of the medical rescue demand [29], the prediction of the emergency material demand [9][10][11][12][13][14][15], fre rescue prediction [30], emergency rescue location model [31], emergency rescue service model [32], and rescue performance [33].…”