Numerical Analysis of Evacuation Start in Pangandaran

Tsunami evacuations plan should consider the behavior of local people. In this study tsunami evacuation start was analyzed using tsunami evacuation simulation consist of evacuee generation and evacuee behavior model. Pangandaran west beach was selected as the target area due to its popularity as a tourist spot and fishery activities in West Java. Evacuation simulations were conducted using 500 evacuations agents with tsunami shelter and grand mosques as goal for the safer place. A total of six evacuation scenarios were made using a different set of evacuation triggers parameter value with the combination of influence weight and effective range. The simulation result indicates that the influence weight which made 57% of people start evacuation immediately after the earthquake happened showed an instantaneous evacuation. Simulation result that was using lower influence weight and lower exposure range showed a more gradual tsunami evacuation. The simulation gave promising results that Pangandaran people could be safely evacuating if they raise their awareness and preparedness. The low-cost simulations that were used in this study provide an insight into the behaviors of Indonesians during disaster evacuation and might use as support for tsunami evacuation planning. However, to produce more satisfactory result we need to conduct field survey and tsunami drill to gain more information of people behavior during tsunami evacuation.

Almost Linear Time Algorithms for Some Problems on Dynamic Flow Networks

Motivated by evacuation planning, several problems regarding dynamic flow networks have been studied in recent years. A dynamic flow network consists of an undirected graph with positive edge lengths, positive edge capacities, and positive vertex weights. The road network in an area can be treated as a graph where the edge lengths are the distances along the roads and the vertex weights are the number of people at each site. An edge capacity limits the number of people that can enter the edge per unit time. In a dynamic flow network, when particular points on edges or vertices called sinks are given, all of the people are required to evacuate from the vertices to the sinks as quickly as possible. This chapter gives an overview of two of our recent results on the problem of locating multiple sinks in a dynamic flow path network such that the max/sum of evacuation times for all the people to sinks is minimized, and we focus on techniques that enable the problems to be solved in almost linear time.

EVACUATING ORANGE COUNTY, CALIFORNIA, IN ABOUT ELEVEN (11) SECONDS

Orange County, California, residents must evacuate when there is a crisis at the San Onofre nuclear power plant in San Clemente, California. They must travel roughly north and east over safe roads. Depending on their location in Orange County (OC), residents will travel to the closest of four (4) waypoints located on the border between OC and neighboring counties. Once a waypoint is reached, evacuees can travel in any direction except back toward OC. The approximate driving distance algorithm is used to suggest a possible waypoint for each address—business or residential. The approximate driving distance algorithm makes this evacuation planning possible, as it takes only around eleven (11) seconds on a state-of-the-art laptop to route 1.1 to 1.2 million addresses to waypoints. Using actual driving distances would take too long and be too expensive, taking approximately fifty-three (53) days on the same platform. The waypoint suggestions are just that: suggestions. In some cases, the approximate driving distance algorithm might not choose the closest waypoint.

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

Humanitarian supply chain management: modeling the pre and post-disaster relief operations

Purpose This study proposed a mathematical model for decision-making in the pre- and post-disaster phases. This research aims to develop a mathematical model for three important fields in the context of humanitarian logistics; stock prepositioning, facility location and evacuation planning in the humanitarian supply chain (HSC) network design. Design/methodology/approach This study applied three optimization techniques; classical approach (CA), pattern search algorithm (PSA) and Genetic Algorithm (GA) to solve the proposed mathematical model. The proposed mathematical model attempts to minimize the total relief items supply chain cost and evacuation chain cost of the HSC. A real case study of cyclone Fani, 2019 in Orissa, India is applied to validate the proposed mathematical model and to show the performance of the model. Findings The results demonstrate that heuristic approach; PSA performs better and optimal solutions are obtained in almost all the cases as compared to the GA and CA. Research limitations/implications This study is limited to deterministic demands in the affected regions, and different scenarios of the disaster events are not considered. Social implications The finding reveals that the proposed model can help the humanitarian stakeholders in making decisions on facility location, relief distribution and evacuation planning in disaster relief operations. Originality/value The results of this study may offer managerial insights to practitioners and humanitarian logisticians who are engaged in HSC implementation.