Enhancing Urban Planning Through Improved Connectivity: A Genetic Algorithm Approach for Optimal Service Placement

In this paper, a review of existing methods for optimal service placement to meet demand has been conducted. A problematic issue was identified in the form of insufficient flexibility of existing solutions for urban planning and development tasks in terms of optimal coverage location problem. The hypothesis that small improvements in connectivity between neighborhoods can significantly reduce the number of optimally placed services was confirmed. A sub-optimal solution was obtained using a genetic algorithm. As a result, recommendations were proposed to improve the transport connectivity between specific neighborhoods for the calculated time interval, which will reduce needed amount of additional facilities to fulfill the demand. The main contribution of this paper is to apply connectivity optimization and optimal service location algorithms together, resulting in a reduction in the number of services required.