Heuristic Route Optimization Using Saving Matrix and Nearest Neighbor: Case Study at PT Harapan Jaya Multi Bisnis, Makassar - Siswanti, Tutik; Fitrina, Rehani (Indonesian Scientific Publication, 2025)
Indonesia faces disproportionately high logistics costs compared to regional and global peers. This study applies Saving Matrix and Nearest Neighbor algorithms to optimize delivery routes at PT Harapan Jaya Multi Bisnis in Makassar, a key logistics hub in Eastern Indonesia. Using operational data from 2022–2023, the research consolidated 12 delivery routes into 5 optimized routes. The optimization reduced the total delivery distance from 2,772 km to 1,967 km, saving 805 km (29%), and lowered distribution costs by approximately Rp 3.5 million every five working days, resulting in a 70% increase in cost efficiency. These findings highlight the practical benefits of heuristic algorithms in addressing urban logistics inefficiencies under infrastructure constraints. However, the study is limited by reliance on company operational records and does not account for external variables such as fuel price fluctuations or seasonal demand surges. The results provide a replicable framework for logistics firms and policymakers seeking data-driven strategies to reduce logistics costs in Indonesia.