Data Analytics Platform with Last-Mile Delivery Decision Support for PWDs Using Metaheuristics Optimization

Modern e-government systems are moving towards becoming inclusive. Especially with systems concerning social services, considering Persons with Disabilities (PWDs) is essential. However, social service delivery systems have yet to fully benefit from the value and impact of data science for insight generation and decision support. This paper introduces a social service analytics and mission planning system (SSAMPS). The data analytics platform presented in this paper enables descriptive analytics for PWDs in local communities and a decision support system for last-mile delivery planning. Through a secure and regulation-compliant information system, descriptive analytics is possible by providing a data visualization tool on the demographic, geographic, and economic status of PWDs in a community. The decision support system includes a last-mile delivery optimization for PWD social services-subcommunity ranking concerning a prioritized type of disability and solving for Hamiltonian paths using traditional and metaheuristic methods. Acceptance tests done with key stakeholders and users of a target local community show apparent acceptance of the developed system. Experimental results for the last-mile delivery optimization show competent cost quality and optimization latency for strategic and operational use. Optimization for strategic usage has a worst-case latency of 659.19 seconds, while operational usage has a worst-case latency of 452 milliseconds.