Optimization of disaster management vessel networks 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. This study focuses on natural hazards such as earthquakes, tsunamis, volcanic eruptions, 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 disaster-prone areas and the locations of available ships, resulting in delayed emergency response times and higher disaster management costs. In addition to TNI ships, the government has vessels from the National Search and Rescue Agency (BASARNAS) and the Indonesian Maritime Security Agency (BAKAMLA) that could be utilized for disaster management. There are also situations where certain response functions cannot be effectively performed by ships, leading to inadequate assistance for disaster victims and potentially increasing fatalities. This research aims to optimize the use of existing ships for disaster management by considering operational costs and coverage areas through the application of the Genetic Algorithm (GA) method. GA is used to identify the optimal combination of ships that minimize costs and maximize coverage areas. The findings of this study provide several ship combinations suitable for responding to natural disasters in Indonesia, which can serve as valuable input for the government in enhancing disaster management efforts.