Optimization of disaster management vessel network in integrated disaster management governance in Indonesia using genetic algorithm

Abstract

Indonesia is highly susceptible to natural disasters due to its location at the convergence of three major tectonic plates: The Indo-Australian, Eurasian, and Pacific plates. These disasters significantly impact the nation's economic development. The study focuses on natural hazards such as earthquakes, tsunami, volcanic eruption, landslides, floods and flash floods. Currently, maritime disaster management primarily involves ships from The Indonesian National Armed Forces (TNI). However, this often leads to mismatches between disasters-prone areas and the location of available ships, resulting in delayed emergency responses times and higher disasters management costs. In addition to TNI ships, the government has vessels from the National Search and Rescue Agency (BASARNAS) and The Maritime Security Agency (BAKAMLA) that could be utilized for disaster management. There are also situation where certain response functions cannot be effectively performed by ships, leading to inedaquate assistance for disaster victims and potentially increasing fatalities. This research aims to optimize the use of existing ships for the disaster management by considering operational costs and coverage areas through the Application of Genetic Algorithm (GA) method. GA is used to identify the optimal combincation of ships that minimize the cost and maximize coverage areas. The findings of this study provide several ships combination suitable for responding to natural disasters in Indonesia, which can serve as valuable input to government in enchancing disasters management efforts.