Web Based Distributor Management System With Delivery Optimization Function

Abstract

The growing necessity for efficient distribution management systems for the FMCG sector has set in sharp light the severe inadequacies of currently available technologies, primarily the optimization of route delivery. The project bridges gaps in currently available Distributor Management Systems (DMS) through the development of a Web-Based Distributor Management System with an embedded Delivery Optimization feature. Utilizing AI-enabled route optimization, the system optimizes delivery timings, reduces operating costs, and increases service levels for small and medium enterprises (SMEs) in Sri Lanka's FMCG sector. The system integrates real-time management of orders, tracking of inventory, and dynamic routing planning powered by Google Maps and machine learning for determining optimum delivery routes with factors such as traffic patterns, ratings of the shop, and distance. The study is a thorough evaluation of existing DMS platforms, identifies deficiencies in delivery optimization, and suggests a tailored solution that enhances distributors' productivity and profitability. The study incorporates the concepts of software engineering, operations research, and data analysis with the potential to significantly enhance operational efficiency and sustainability of SME distributors. The system is tested against the business metrics of the key performance indicators (KPIs), including delivery time, cost savings, and carbon footprint, to ensure its alignment with business and environmental objectives.