Evaluating Heuristic and Optimization-Based Methods for Minimum-Cost Distribution Flow Allocation Through Discrete-Event Simulation

Background: This study evaluates heuristic and optimization-based methods for minimum-cost distribution flow allocation using discrete-event simulation. Methods: Four distribution networks in Ecuador were modeled in FlexSim 2027, comprising a hypothetical factory–warehouse system and three fuel distribution networks with 147 to 1872 potential connections. Seven allocation strategies were compared across three demand levels (25%, 50%, and 100%), using 31 paired replications. Performance was evaluated in terms of unit cost and algorithm execution time, using Gurobi as the optimization reference. Results: In the factory–warehouse network, Northwest Corner produced a mean unit cost of USD 11.14, compared with USD 9.03 for Gurobi, representing a 23.3% increase. In the Diesel Premium network, these costs were USD 3.1212 and USD 3.1094 per gallon, respectively. Northwest Corner consistently required the shortest execution times (314–826 ms), whereas Gurobi required 3330–44,570 ms. Among strategies achieving costs equal to, lower than, or not significantly different from Gurobi, OR-Tools ranked fastest in nine of twelve configurations, while Minimum Cost ranked first in the remaining three. Conclusions: These findings highlight the importance of obtaining minimum-cost allocations while considering computational efficiency when selecting methods for distribution networks of different sizes.