A Multi-Type Ship Allocation and Routing Model for Multi-Product Oil Distribution in Indonesia with Inventory and Cost Minimization Considerations: A Mixed-Integer Linear Programming Approach

Background: Indonesia is an archipelagic country with 17,508 islands spread over the Pacific and Indian Oceans, with thousands of inter-island routes requiring a large and engaged fleet. The vast expanse of the country also leads to challenges related to optimal fleet coverage, routing, and oil distribution while maintaining cost-effectiveness and reliable supply. Methods: This study combined a mixed-integer linear-programming (MILP) model with a response surface methodology (RSM) approach to optimize vessel assignment, vessel routes, and inventory control simultaneously and comprehensively across three regional clusters (i.e., Western, Central, and Eastern Indonesia). The model takes into account a fleet of 28 vessels (13 medium range [MR] and 15 general purpose [GP]) that can distribute three oil products: gasoline, diesel, and kerosene. Results: The optimized solution yields 100% service reliability at an operational cost of $ 2.83 million per month—far lower than currently operating services. The model is robust against variations in demand (±20%), port congestion (±50%), and changing fuel prices (±50%), which is confirmed by a sensibility analysis. The close correlation coefficient (0.987) between the MILP and RSM results confirms the framework’s accuracy. At the same time, the critical performance factors were found to be vessel speed (13.5 knots), fleet size, and port operation time. Conclusions: The study offers a cost-efficient and data-intensive model that could be implemented as a maritime logistics framework, as well as potential areas for future work and insight for relevant stakeholders. Future research will have to integrate real-time data fusion, mainly due to the need for environmental and stochastic modeling methods to foster operational resilience in dynamic maritime business ecosystems.