面对可能发生的海啸,基于gis的燃料配置优化——以巴东市为例

Rahmad Inca Liperda, Anisha Rizqy Aulya, I. Sukarno, Mirna Lusiani, N. Sirivongpaisal
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摘要

据预测,明打威大逆冲带将引发海啸,对社会和环境造成巨大影响。巴东市位于震中的沿海地区,预计在未来的灾害中很容易受到冲击。为了提供有效的灾害对策以尽量减少损失和痛苦,这个问题已逐渐变得重要起来。由于燃料是灾后最重要的物品之一,本研究旨在提出巴东市的救灾规划,特别是在燃料的位置分配决策,以应对可能的海啸造成的影响。在本研究中,利用基于地理信息系统(GIS)的优化来生成适当数量的设施及其分配能力,以便在紧急时期为几个需求点(例如医院和难民营)提供服务。本文首先根据灾害对策机构制定的最坏情况,考虑潜在淹没面积,确定安全区域内不可通行路径和候选设施的可能性。通过p -中值分析,本文推荐了9个战略设施来处理关键时期的18个需求点。这项研究提供了一个令人兴奋的机会,以全面获得合适的设施,以满足灾后的燃料需求。由于实际情况的限制,本文可能会进一步改进为考虑紧急情况下实时情况的决策支持系统(DSS)。
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A GIS – BASED OPTIMIZATION FOR THE FUEL LOCATION-ALLOCATION TO FACE THE PROBABLE TSUNAMI: CASE OF PADANG CITY
The Mentawai Megathrust is predicted to cause a tsunami with the tremendous effects to societies and environments. As the coastal area located across the epicenter, Padang City is expected to have a high vulnerability to be surged by this future hazard. This issue has gradually grown in importance to provide an effective disaster countermeasure for minimizing losses and suffering. As the fuel is one of the most critical items required in the aftermath of disaster, this study seeks to propose the disaster relief planning in Padang City, particularly in the fuel location-allocation decisions to cope with the effects caused by the probable tsunami. In this research the Geographic Information System (GIS)-based optimization is utilized to generate the appropriate number of facilities as well as its allocated capacity to serve several demand points (e.g. hospitals and refugee camps) during the emergency periods. This paper initially considers the potential inundation area based on the worst-case scenario developed by the disaster countermeasure agency to identify the likelihood of the impassable paths and the candidate facilities in the safe zone. By using P-Median analysis, this work recommends 9 strategic facilities to handle 18 demand points during the critical periods. This study provides an exciting opportunity to comprehensively obtain the suitable facilities in order to fulfill the fuel needs in the disaster aftermath. Due to practical constraints, this paper may be further improved to be Decisions Support Systems (DSS) with the consideration to the real time conditions during emergency periods.
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