Using Linear Programming to Determine Sustainable Service Locations in Diyala Governorate

Abstract

The rapid advancement of modern technology and artificial intelligence has significantly transformed urban systems and increased the need for intelligent and sustainable urban planning. Rapid population growth, urban expansion, and the increasing complexity of transportation and service networks have created major challenges for city planners in determining optimal locations for service facilities that can efficiently meet the needs of urban populations. Proper facility location planning plays a crucial role in improving service accessibility, reducing operational costs, and enhancing the overall efficiency of urban infrastructure.This study aims to determine optimal and sustainable locations for establishing service centers such as emergency response facilities and waste management centers. The research employs quantitative approaches that integrate statistical analysis with operations research techniques, particularly linear programming, along with artificial intelligence methods to support decision-making in facility location optimization.The empirical application focuses on Diyala Governorate in Iraq, which consists of several districts and sub-districts distributed across a wide geographical area. By analyzing the spatial structure of the region, including transportation networks and residential distribution, the study identifies suitable locations for service facilities capable of providing rapid response in emergency situations. The proposed framework contributes to improving service efficiency, reducing response time and operational costs, and supporting sustainable urban development and smart city planning.